# jamgate

**Category:** 🧠 Knowledge & Memory  
**Repository:** https://github.com/amirj4m/jamgate  
**Views:** 0  
**Installs:** 0  
**Upvotes:** 0  
**Directory Page:** https://allmcps.com/mcp/jamgate

## Description
A neutral memory quality-gate MCP server: save_memory, recall_memory, forget_memory over stdio.

## Claude Desktop Quick Installation
Heuristic fallback — verify the package name and runner against the repository README before running it. Uses `npx` (confidence: low):

```json
"mcpServers": {
  "jamgate": {
    "command": "npx",
    "args": ["-y","jamgate"]
  }
}
```

## Documentation & README

# Jamgate

[![CI](https://github.com/amirj4m/jamgate/actions/workflows/ci.yml/badge.svg)](https://github.com/amirj4m/jamgate/actions/workflows/ci.yml)
[![npm version](https://img.shields.io/npm/v/jamgate.svg)](https://www.npmjs.com/package/jamgate)
[![license: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](./LICENSE)

> Every AI tool I use keeps its own memory, so I kept re-introducing myself to all of them.
> Jamgate is one memory file on my machine that any MCP client can read and write, with a
> quality gate in front deciding what actually gets written. It runs locally and has one
> runtime dependency.

I built it for myself and I'm the only person who has used it in anger, which is worth
knowing before you read the rest. [What it can't do](#honest-limits) is a section, not a
footnote.

One command wires it into every MCP client on your machine:

```bash
npx jamgate setup
```

[![Add to Cursor](https://img.shields.io/badge/Add%20to-Cursor-000?logo=cursor&logoColor=white)](cursor://anysphere.cursor-deeplink/mcp/install?name=jamgate&config=eyJjb21tYW5kIjoibnB4IiwiYXJncyI6WyJqYW1nYXRlIl19)
 •  one-click **Claude Desktop** bundle → the `.mcpb` on the [latest release](https://github.com/amirj4m/jamgate/releases/latest)

## Why a gate and not just a store

Sharing memory between agents turns out to be the easy half. I had a working shared store
early on and the problem it created was worse than the one it solved: within a week it was
full of "jam is on a call", the same fact three times in slightly different words, and a
stale preference from a month earlier being handed to an agent as though it were current.

The clearest public example of where this ends up is
[mem0 issue #4573](https://github.com/mem0ai/mem0/issues/4573), where a user audited their own
production store of 10,134 entries by hand. The detail I keep coming back to is this one: **808
entries asserting "User prefers Vim". Nobody in that system used Vim.** The extraction model
hallucinated it once, it got stored, it came back in the next session's recall context, and the
pipeline re-extracted it from its own output as though it were a fresh fact.

Read that report carefully before you lean on it, though. It is one person, one agent, 32 days,
and a 2-billion-parameter local model did the extraction for the first 20 of those days. The
headline "97.8% junk" is dominated by that weak model; in the batch extracted by a frontier
model the rate was 89.6%. The issue is now closed, and a mem0 maintainer has since described
changes shipped in April 2026 aimed squarely at these problems.

So I don't want to lean on the percentage, and this README used to. The part that survives all
of those caveats is structural, and no model upgrade fixes it: **if there is nothing between
extraction and storage, a hallucination that gets stored once will be re-extracted forever.**
A better model changes how articulate the junk is. Sharing that memory across every agent you
own just distributes it faster.

So Jamgate sits in the write path and decides what gets stored:

```
                 without a gate                          with Jamgate
   ┌──────────────────────────────────┐   ┌──────────────────────────────────────┐
   │ "remember I'm on a call"          │   │ ✗ rejected — not durable             │
   │ "I use Windows"  ← from 6mo ago   │   │ ⇄ superseded — "I use Linux" wins    │
   │ "I use Windows"  (again)          │   │ ✗ duplicate — already known          │
   │ "I use Linux"                     │   │ ✓ saved — durable, changes answers   │
   │ "my name is Sam" (agent guessed)  │   │ ⚠ conflict — lower trust, ask first  │
   └──────────────────────────────────┘   └──────────────────────────────────────┘
     it all piles up, forever                 small, and still true
```

It runs as an [MCP](https://modelcontextprotocol.io) server, so any MCP client (Claude Code,
Claude Desktop, Cursor, and seven others) talks to the same memory file on your machine.

```
Agent → [ Jamgate quality gate ] → local store (~/.jamgate/memory.json)
        save_memory / recall_memory / forget_memory
```

## The gate layers

A memory is kept if it is still true after this session and would change a future answer.
Cheapest checks run first:

| Layer | What it does |
| --- | --- |
| **Rule pre-filter** | Drops obvious non-durable noise before it reaches the store: fragments, pleasantries, placeholder text (`test`, `foo bar`), and anything that isn't a claim about you. |
| **Credential refusal** | Refuses to store secrets. API keys (`sk-…`, `AKIA…`, `ghp_…`, JWTs, PEM blocks), password assignments, and high-entropy tokens next to credential wording are rejected with a reason — and kept out of the decision log too. A git sha or UUID in ordinary prose passes untouched. |
| **Question filter** | A question asks *for* memory, it isn't memory. `how much is jam's rent?` is refused; a rhetorical question inside a longer fact is not. |
| **Transience filter** | Statements pinned to this instant ("it's raining right now") are refused unless you type them as `state`, where a short TTL ages them out on their own. |
| **Agent salience** | Uses the calling agent's own understanding as the main "is this worth remembering?" filter — no second LLM call of its own. |
| **Thin classifier** *(built, and inert on most clients today)* | For the few saves a rule finds genuinely ambiguous, the gate asks your agent's own model one closed question over MCP sampling, so there is no API key, no vendor and nothing to pay for. It catches two things a rule cannot: text that announces itself as scaffolding (`safe to delete`, `temporary test entry`), and a long `state` save that is really a permanent fact and would quietly expire in two days. It can only tighten a verdict, never loosen one, and it never sees any memory but the one being saved. **Sampling is optional in MCP and most clients do not implement it. Claude Code declares `roots` and `elicitation` and no `sampling`, so for most people today this layer never runs at all and the gate is rules-only.** See [Honest limits](#honest-limits). |
| **Exact dedup** | Identical facts are never stored twice. |
| **Time-aware supersession** | Every memory is a timestamped event; a newer fact retires an older one on the same `subject` by recency — no contradiction pile-up, and it never throws your own stale words back at you. |
| **Trust hierarchy** | A lower-trust source (an agent's guess) can't silently overwrite a higher-trust fact (something you said explicitly). The gate refers the conflict back to you instead. |
| **Semantic near-dup** *(optional)* | With local embeddings on, a save that *means* the same as an existing memory returns as a `possible_duplicate` to confirm, rather than piling up. |
| **Related-memory hint** *(optional)* | Below the duplicate bar but clearly on the same topic, the memory is **stored** and the look-alike is named, so the agent can re-save with a shared `subject` if it was really an update. A hint never retires anything. |
| **Type-based expiry** | Volatile state ages out (~2 days) while identity never does, so recall stays current automatically. **Expiry hides a memory; it never destroys one you asked for** — compaction skips every `user-explicit` / `user-confirmed` record permanently, and `jamgate expired` lists them with no deletion deadline. |
| **Write-time lifespan check** *(needs MCP elicitation)* | If your agent files something *you* asked it to remember as short-lived state, the gate asks **you** — once, at the moment of saving, showing the memory and the date it would disappear — and stores your answer. This exists because it happened to my own store: two facts I confirmed were filed as 2-day state, went dark unannounced, and were four weeks from deletion. Replayed on my real gate log it fires on **3 of 21 save decisions (14.3%)** and stays silent on every agent-inferred state note. (That figure was previously given as 17.5%, measured against a gate log that turned out to be 95.5% test fixtures; it is re-derived here against the 25 genuine decisions — see D-078.) **Claude Code declares `elicitation`, so this one actually runs.** Off with `JAMGATE_LIFESPAN_PROMPT=off`. |

Every rejection comes back with a reason the calling agent can act on. This matters more than
it sounds: the agent is the only party in a position to fix the call, and a bare "rejected"
just teaches it to retry with slightly different wording until something sticks.

Note what is *not* in that table: nothing here understands your memory. These are rules,
regexes and cosine thresholds. See [Honest limits](#honest-limits).

## Honest limits

Read this before the feature list, not after it. Everything below is measured or observed,
and none of it is fixed yet.

**Recall often puts the wrong memory first.** On my own store — 12 real memories, 17 queries
I wrote — the right memory came back at rank 1 in **10 of 17** cases, and appeared anywhere
in the top 5 in 13. Turning on the optional embeddings *used* to make this worse than leaving
them off; that's fixed, but "the answer is in there somewhere" is still an accurate
description of recall on a store of any size. This is the weakest part of the project and
the thing I'd fix next.

One specific failure inside that has been fixed, because it was worse than "imprecise": a
memory past its freshness window could outrank the memory that corrected it. Asking the same
question about money six ways, **four of six returned the superseded figure first**. Freshness
is now a tier applied before relevance, so nothing past its window can outrank anything inside
one — the same six phrasings now return the correct figure **six times out of six**, with the
ordinary top-1 baseline unchanged (14/17 before and after, identical misses). It is not "newest
wins": an `identity` fact never expires, so it is never stale and ranks on relevance exactly as
it did. What is *not* fixed is the general ordering problem above, or contradiction detection
across two different subjects — two live records can still assert different numbers for the same
thing and nothing notices. For scale: Letta measured plain files plus `grep` at 74.0% on LoCoMo
against Mem0's 68.5%, and I have no reason to think Jamgate's retrieval would beat either.
See [How it compares](#how-it-compares), where `grep` gets its own column.

**Ranking has produced a wrong answer about money, not just a wrong order.** Asked "how much do
I still owe on the motorbike", recall returned a 6 August balance at rank 1 and missed the 8
August one entirely — both live, both in the store, €250 apart. Across six natural phrasings of
that question the stale figure won four. This is the same weakness as the row above, but it is
worth stating separately because "the answer is in there somewhere" stops being an acceptable
description once the answer is someone's finances. See D-077.

**A name written in one script cannot be found by its spelling in the other.** Matching is
token-based and script-literal, with no transliteration bridge. Measured on my own store, on
two names recorded in Latin inside a Persian-speaking user's memory: `Rahman` and `Iraj` each
return the right record at **rank 1 for every natural English phrasing** (11 of 12 at rank 1,
one at rank 2) — and `رحمان`, `ایرج`, `بدهی رحمان`, `بدهی ایرج` return **nothing at all**, 0 of 4.
Cross-script queries only work when the record happens to share tokens in the query's script.
For a bilingual user this is data-loss-equivalent: the memory is there, correct, and
unreachable in half the languages they actually type. Not fixed — see D-075 for the scope.

**Nobody outside me has installed it.** Many releases, ten supported clients, one user.
I've simulated a cold install (fresh `HOME`, empty npm cache, published package rather than
my working copy) and it held up, but simulation is not a stranger on their own machine.

**macOS and Windows have never actually been run.** Their config paths are unit-tested and
CI is Linux-only. If you are on a Mac and `jamgate setup` writes to the wrong place, you are
the first person to find out. Please open an issue.

**Embeddings only attach when a memory is saved.** Install the optional semantic package
today and every memory you saved before that stays invisible to semantic recall until you
save it again. There is no `reindex` command. This is a straightforward gap, not a hard
problem, and it isn't done.

**"Store-agnostic" is a seam, not a feature.** Everything above `src/store/` depends on a
`MemoryStore` interface rather than a concrete backend, which is a real design property you
can check in the source. But the bundled file store is the only implementation. There is no
mem0 adapter, no Graphiti adapter, and **no way for you to point Jamgate at your own store
today.** If a future write-up of mine implies otherwise, this line is the correct one.

**The quality judgments are rules and numbers, not understanding.** The gate cannot tell that
"moved to Berlin last spring" and "no longer lives in Athens" are the same event. It matches
subjects, compares cosines against thresholds I set from measurements, and applies regexes.
It is genuinely good at the mechanical cases — exact duplicates, credentials, recency on a
shared subject — and blind to anything requiring judgment.

**The thin classifier ships in this release and does nothing on most machines.** It is built
and it is measured: 96.4% accuracy (27 of 28) on a labelled corpus, no real memory refused in
any recorded run, and it routes about 30% of decisions. But it works by asking the calling
client's own model over MCP sampling, sampling is optional in the protocol, and most clients
have not implemented it — Claude Code declares `roots` and `elicitation` and no `sampling`.
So unless your client samples, this layer never runs and your gate is the rules-only gate
described above. I have not seen it change a single real save of my own, because every client
I use is in that group. Treat the measurements as evidence the thing works when it is asked,
not as evidence it is working for you.

**One JSON file, read whole on every operation.** At my ~60 records that is free. There is no
index and no pagination, so at some size it stops being free. It is now measured rather than
guessed at (D-078), with embeddings off, growing a store to 10,000 records:

| records | file | one save | one recall |
|---:|---:|---:|---:|
| 100 | 0.1 MB | 5 ms | 12 ms |
| 1,000 | 0.6 MB | 19 ms | 71 ms |
| 5,000 | 3.1 MB | 52 ms | 399 ms |
| 10,000 | 6.1 MB | 110 ms | 758 ms |

Nothing breaks — no crash, no corruption, no lock failure; it degrades linearly. Recall hurts
first, because it scores every record: perceptible past ~2,000 records and unpleasant past
~6,000. With embeddings on, every save also embeds and the near-duplicate scan compares all
vectors, so treat these as the optimistic bound.

**Semantic search is English-only.** The bundled model is `all-MiniLM-L6-v2`. On other
scripts its similarity degenerates into "is this the same language" (the Greek for *bicycle*
scored 0.62 against an unrelated Greek memory), so non-Latin text is deliberately not
embedded at all and falls back to lexical matching, which does work in every script.

**A memory is text, and recall puts it into your agent's context.** The gate decides whether
something is worth keeping, not whether it is safe to act on. If a memory contains
instructions, those words come back verbatim on the next recall, in a place the model reads.
That is true of every memory system. Jamgate narrows the surface — it never scrapes screens,
never mines chat logs, refuses credentials, and only writes on an explicit `save_memory`
call — but it cannot make text inert. Treat the store as trusted input and look at what goes
in; `jamgate export` prints all of it.

Remote mode has its own set of limits, listed under [Remote mode](#remote-mode-limits).

## Quick start

Jamgate runs **locally** — your memory never leaves your machine. Requires Node.js 20+.
No install step: `npx` fetches and runs it on demand.

### Option A — `npx jamgate setup` (recommended)

One command detects the MCP clients installed on your machine (Claude Code, Claude Desktop,
Cursor, Windsurf, Gemini CLI, VS Code / Copilot, Cline, Roo Code, OpenCode, Zed) and wires
Jamgate into each:

```bash
npx jamgate setup
```

It is **safe to run**: idempotent (running it twice changes nothing), it never touches any
server entry but its own, and it backs up each config file to `<file>.jamgate-backup` before
writing. A plain `setup` (local stdio) will also **never silently overwrite a remote (`--remote`)
wiring** — it leaves that client as-is and tells you so; pass `--force` to downgrade it on
purpose. Useful flags:

```bash
npx jamgate setup --dry-run                          # show what would change, write nothing
npx jamgate setup --remote https://you/mcp --token … # wire HTTP transport (see Remote mode)
npx jamgate setup --force                             # overwrite even a remote wiring with local stdio
npx jamgate status                                    # show which clients are wired + where the store lives
npx jamgate --help                                    # every command and environment variable
```

If `setup` finds no clients, that is normal on a machine where the client has been installed
but never launched — a client writes its config on first run. Start it once, then re-run
`npx jamgate setup`.

Restart your client(s) afterwards. On Claude Code, when the `claude` CLI is present, setup
uses `claude mcp add` under the hood; otherwise it merges `~/.claude.json` directly.

### Option B — per-client manual

Prefer to wire it yourself? Each client is a small config change.

**Claude Code:**

```bash
claude mcp add jamgate -- npx jamgate
```

**Claude Desktop** — one-click: download the `.mcpb` bundle from the
[latest release](https://github.com/amirj4m/jamgate/releases/latest) and open it (Claude
Desktop → Settings → Extensions; the bundle is unsigned, so you may see an "unverified"
prompt). Or add to `claude_desktop_config.json` (Settings → Developer → Edit Config):

```json
{
  "mcpServers": {
    "jamgate": {
      "command": "npx",
      "args": ["jamgate"]
    }
  }
}
```

**Cursor** — click the **Add to Cursor** badge at the top, or add to `~/.cursor/mcp.json`
(or `.cursor/mcp.json` in a project):

```json
{
  "mcpServers": {
    "jamgate": {
      "command": "npx",
      "args": ["jamgate"]
    }
  }
}
```

**Windsurf** — add the same `mcpServers` block to `~/.codeium/windsurf/mcp_config.json`.

**Gemini CLI** — add the same `mcpServers` block to `~/.gemini/settings.json`.

**Cline / Roo Code** — add the same `mcpServers` block to the extension's MCP settings file
(Cline: `.../globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json`; Roo:
`.../globalStorage/rooveterinaryinc.roo-cline/settings/mcp_settings.json`), or use each
extension's "Configure/Edit MCP Servers" button.

**VS Code (Copilot)** — add to the user `mcp.json` (Command Palette → **MCP: Open User
Configuration**). VS Code uses a `servers` key and an explicit `type`:

```json
{
  "servers": {
    "jamgate": { "type": "stdio", "command": "npx", "args": ["jamgate"] }
  }
}
```

**OpenCode** — add to `~/.config/opencode/opencode.json` under the `mcp` key (note the single
`command` array and `enabled` flag):

```json
{
  "mcp": {
    "jamgate": { "type": "local", "command": ["npx", "jamgate"], "enabled": true }
  }
}
```

**Zed** — add to `settings.json` under `context_servers`:

```json
{
  "context_servers": {
    "jamgate": { "command": "npx", "args": ["jamgate"] }
  }
}
```

#### Supported agents

`jamgate setup` auto-wires every agent below whose MCP config it can merge **losslessly** —
each entry shape is verified against the vendor's official docs. Agents whose config lives in a
non-JSON format I can't safely round-trip (TOML / YAML) are listed as **manual** with the
one-liner to add yourself.

| Agent | Config file | `setup` | Remote (`--remote`) |
| --- | --- | --- | --- |
| Claude Code | `~/.claude.json` | ✅ auto | ✅ |
| Claude Desktop | `claude_desktop_config.json` | ✅ auto | connectors UI |
| Cursor | `~/.cursor/mcp.json` | ✅ auto | ✅ |
| Windsurf | `~/.codeium/windsurf/mcp_config.json` | ✅ auto | ✅ |
| Gemini CLI | `~/.gemini/settings.json` | ✅ auto | ✅ |
| VS Code (Copilot) | `<Code>/User/mcp.json` | ✅ auto | ✅ |
| Cline | `.../saoudrizwan.claude-dev/settings/cline_mcp_settings.json` | ✅ auto | ✅ |
| Roo Code | `.../rooveterinaryinc.roo-cline/settings/mcp_settings.json` | ✅ auto | ✅ |
| OpenCode | `~/.config/opencode/opencode.json` | ✅ auto | ✅ |
| Zed | `~/.config/zed/settings.json` | ✅ auto | ✅ |
| Codex CLI | `~/.codex/config.toml` (TOML) | manual¹ | — |
| Goose | `~/.config/goose/config.yaml` (YAML) | manual¹ | — |
| Continue | `~/.continue/config.yaml` (YAML) | manual¹ | — |

¹ **Manual** — these use TOML/YAML; rather than risk mangling comments or formatting I don't
auto-edit them. Add Jamgate by hand: **Codex CLI** →
`[mcp_servers.jamgate]` with `command = "npx"` and `args = ["jamgate"]` in `~/.codex/config.toml`;
**Goose** → a `stdio` extension under `extensions:` with `cmd: npx` / `args: ["jamgate"]`;
**Continue** → an `mcpServers:` list entry with `command: npx` / `args: [jamgate]`.

> For agents that live in a shared, comment-friendly settings file (Gemini, OpenCode, Zed),
> `setup` will **skip** rather than overwrite a file it can't parse as strict JSON — so a
> `//`-commented `settings.json` is never clobbered; add the block by hand in that case.

Restart the agent. It now has three tools:

- **`save_memory`** — store a durable fact. The gate rejects junk, drops exact
  duplicates, supersedes outdated facts by recency (pass a `subject` like
  `operating-system` so a newer fact retires the older one — or let the gate derive one),
  and refers trust conflicts back to you. Subjects are **lowercase and hyphenated**; dots,
  underscores and spaces fold to hyphens, so `editor.theme` and `editor-theme` are one key.
- **`recall_memory`** — fetch what's known, relevant to a query (active facts only).
- **`forget_memory`** — delete a memory by the id `recall_memory` printed (the full id, or an
  unambiguous prefix of 8+ characters).

Volatile memories age out of recall on a TTL, so a fact you saved can stop being returned
without being deleted. `jamgate expired` shows exactly what recall is hiding and when it will
be compacted away — nothing is modified:

```bash
jamgate expired               # what has aged out of recall but is still on disk
jamgate expired --json        # machine-readable, for a script
```

Your memory lives in `~/.jamgate/memory.json`. Same machine, every agent → one shared
memory. To share one memory across **different** machines and your phone, see
[Remote mode](#remote-mode-self-hosted).

### If you move to a remote instance: retire the local store

The worst failure mode of a memory that lives in two places is that **nothing tells you**. One
client stays wired to the local stdio store, every save there succeeds, and you accumulate a
second memory you don't know about. That happened to me: four days, seven memories, found only
by a scheduled check.

Two things now make it loud rather than silent:

```bash
jamgate status                                  # warns ⚠ SPLIT MEMORY if clients disagree
jamgate retire --to https://your-instance/mcp   # the old store refuses writes from now on
```

`jamgate status` compares every wired client and says so when some point at a remote instance
while others write locally. `jamgate retire` marks the store — so any client that later gets
wired back to it fails with an error naming the real instance instead of quietly writing there.
**Reads keep working and nothing is deleted**, so a retired store is still fully readable; it
just stops being a place new memories can land. `jamgate retire --status` reports the state and
changes nothing.

The marker is written twice, deliberately: inside the store file (so it travels when the file
is copied) **and** as a `<store>.retired` sidecar. The sidecar exists because a Jamgate older
than 0.14.0 serializes the store without the in-file field and silently erases it on the first
write — which is exactly what a stale server did to my own retired store. If the sidecar is
there and the in-file marker is gone, `jamgate status` tells you an old build is still writing
and you need to stop the process, not just remove its config entry.

**Removing a client's config entry does not kill a server it already started.** That is worth
knowing because `jamgate status` reads config files: it will say "no split" while a stale
process keeps serving the old store to a live client.

`jamgate setup` also refuses to add a local store when another client already points at a
remote one, so the split cannot be created by accident (`--force` if you truly want two).

## Agent skill: `memory-discipline`

Wiring in the three tools gives an agent the *ability* to remember. The
**`memory-discipline`** skill teaches it the *habits* — recall before answering,
save one granular durable fact at a time with a specific reused `subject`, never send
secrets, and treat gate verdicts as answers rather than errors to retry. Its rules are
distilled straight from Jamgate's own [decision log](./DECISIONS.md) (D-040…D-045).

It ships in this repo at [`skills/memory-discipline/SKILL.md`](./skills/memory-discipline/SKILL.md)
as a portable [agentskills.io](https://agentskills.io) instruction pack. One command installs it
for every agent the `skills` CLI finds on your machine (it wired 17, including Cursor, Copilot
and Claude Code, on the machine I tested it on):

```bash
npx skills add amirj4m/jamgate
```

The skill is prompt text, not code — it is **not** part of the npm package (the
`files` whitelist ships only `dist`), so it never bloats the runtime install.

## Optional: local semantic search

By default, recall is **fuzzy lexical** matching (stemming, typo-tolerance, trigrams) —
fast, deterministic, and dependency-free, but blind to synonyms. It works in **any script**:
Persian, Greek, Cyrillic, Arabic, Hebrew, Chinese, Japanese and Korean all tokenize and
recall, and accents fold so `café` and `cafe` find each other. (Stemming is English-only, and
Chinese/Japanese are segmented per character rather than per word — good enough to find a term
inside a sentence, not a real word segmenter.) To also match on
*meaning* (so "automobile" recalls a memory about your "car"), install the optional
embedding backend:

```bash
npm install @huggingface/transformers
```

On first use it downloads all-MiniLM-L6-v2 and runs it **entirely on your machine — no text is
ever sent to any cloud AI**. Budget about **90 MB** for that download: this README used to say
"~23 MB, quantized", which was wrong on both counts. Transformers.js fetches the fp32 model by
default and the cached directory measures 87 MB on disk, so on a small VPS or a metered
connection, plan for the real number. With the model in place, recall blends semantic
similarity into the ranking, and a save that means the same as an existing memory comes back as
a `possible_duplicate` for you to confirm. **If the package isn't installed, Jamgate runs on
fuzzy recall and nothing breaks.**

**What to expect from it, measured rather than assumed** ([D-063](./DECISIONS.md)): the
thresholds are set from real cosines on this model over a real store, not from estimates.
Two limits are worth knowing before you install it:

- **Embeddings attach when a memory is saved.** Memories written *before* you installed the
  package have no vector, so they stay on fuzzy recall until they are saved again. There is
  no backfill command yet.
- **Long memories dilute.** The model mean-pools, so a short query against a 500-character
  memory scores lower than against a one-line fact. Synonym reach is strongest exactly where
  the README's example is — short, single-fact memories.
- **English only.** all-MiniLM-L6-v2 is an English model, and on other scripts its
  "similarity" collapses into *"is this the same language"* — measured, with the Greek for
  *bicycle* scoring 0.62 against an unrelated Greek memory. So non-Latin text is deliberately
  **not** embedded: those languages stay on fuzzy lexical recall, which works properly in
  every script. Nothing is lost by installing the package if you write in Persian or Japanese;
  nothing is gained either.

## Namespaces (scopes)

By default Jamgate is single-tenant: one human, one memory. If you need **one instance to hold
several memories that must not blend** — a tutor app with separate subjects, or a small group
sharing an instance — attach an optional **scope** (an opaque label such as `amir/greek`) to a
memory and to each operation:

- **The gate is per scope.** Deduplication, subject supersession, the source-trust conflict
  guard and the semantic near-duplicate check all compare a new memory only against others in
  the **same** scope. Two scopes can hold the same text, the same subject, even contradictory
  facts, without one affecting the other.
- **Recall and forget are strictly scoped.** Recall returns only the requested scope; forget
  resolves an id only within its scope, so one namespace can never read or delete another's
  memory — even with the exact id.
- **Omitting the scope is the normal case.** An absent or empty scope means the single
  `default` namespace, which is exactly how Jamgate behaved before namespaces existed. Nothing
  changes for a single-user setup.

Over MCP, pass `scope` on `save_memory` / `recall_memory` / `forget_memory`. Over the REST API
(below), pass it in the JSON body or as a `?scope=` query parameter. Scopes are just
case/whitespace-folded labels — `user/role` is a useful convention, not a required format.

> Multi-**user** separation (per-person accounts and auth) is a different thing and is not what
> a scope provides: whoever holds the `JAMGATE_TOKEN` can address any scope on that instance. A
> scope is a namespace **within** one token-holder's memory.

## Configuration

All configuration is via environment variables; every one has a sensible default.

| Variable | Default | What it does |
| --- | --- | --- |
| `JAMGATE_STORE` | `~/.jamgate/memory.json` | Path to the memory store file. |
| `JAMGATE_EMBEDDINGS` | auto | `off` disables the semantic layer even if the model is installed. |
| `JAMGATE_DUP_THRESHOLD` | `0.88` | Semantic near-duplicate sensitivity (0–1); higher = stricter. Measured against the real model, true rewordings span ~0.76–0.94 and *different* facts reach ~0.81, so the two overlap — 0.88 deliberately favours never refusing a real memory over catching every reword. |
| `JAMGATE_GATE_LOG` | on | `off` disables the local decision log. |
| `JAMGATE_CLASSIFIER` | on | `off` disables the thin classifier outright — no sampling request is ever sent and the gate runs rules-only. It is already inert on any client that doesn't support MCP sampling. |
| `JAMGATE_CLASSIFIER_TIMEOUT_MS` | `8000` | How long a save may wait for the classifier's answer before giving up and saving as rules-only. A save is never blocked on a model. |
| `JAMGATE_TTL_<TYPE>_DAYS` | per type | Override the freshness window for a memory type, e.g. `JAMGATE_TTL_PROJECT_DAYS=180`. |
| `JAMGATE_HTTP` | off | `1`/`true` enables [remote mode](#remote-mode-self-hosted) (same as the `--http` flag). |
| `JAMGATE_PORT` | `8420` | Port for remote mode (same as `--port`). |
| `JAMGATE_HOST` | `127.0.0.1` | Interface to bind in remote mode. Keep it on localhost behind a reverse proxy. |
| `JAMGATE_TOKEN` | — | Bearer token required in remote mode. The server refuses to start without it. |
| `JAMGATE_OAUTH` | on | In remote mode, serve the [MCP OAuth flow](#adding-to-claudeai-mcp-oauth) so claude.ai / the Claude app can connect. `off` disables it (static-token-only). |
| `JAMGATE_OAUTH_STORE` | `~/.jamgate/oauth.json` | Path to the OAuth state file (registered clients + hashed tokens). |

## Backup & migration

Your memory is one JSON file (`JAMGATE_STORE`, default `~/.jamgate/memory.json`), so a backup can
be as simple as copying it. But `jamgate export` / `jamgate import` do it properly — schema-aware,
and with import passing every record back **through the same quality gate** so a restore or a
machine-to-machine move can't smuggle in duplicates or overwrite a trusted fact.

```bash
# Back up everything (active + superseded history) to a file
jamgate export --output backup.json

# Only the live facts, and pipe it somewhere
jamgate export --active-only > my-memory.json

# Restore / merge into another machine's store (respects JAMGATE_STORE)
jamgate import backup.json

# See exactly what would happen first — nothing is written
jamgate import backup.json --dry-run
```

**Export** writes a `{ schemaVersion, exportedAt, generator, memories }` envelope. Without
`--output` it prints pure JSON to stdout (so it pipes cleanly) and the summary to stderr.

**Import** accepts that envelope *or* a bare JSON array. Each active record is replayed through the
gate — exact-duplicate dedup, time-aware supersession, the trust/contradiction guard, and
near-duplicate detection — instead of being blindly appended, and original timestamps and
provenance are **preserved** (your `createdAt` is never reset). It prints a per-record report
(imported / duplicates skipped / superseded / conflicts flagged / near-duplicates); conflicts and
near-duplicates are surfaced for you to decide, never silently resolved. The whole import is one
atomic transaction — a malformed file is rejected with a nonzero exit and your store is left
untouched. Records already retired (`superseded`) in the source are treated as history and skipped,
not re-activated. See [DECISIONS D-033](./DECISIONS.md).

> Moving a **local** store onto **your own server**? Export locally, copy the JSON up, then
> `JAMGATE_STORE=/data/memory.json jamgate import my-memory.json` on the box (or just place the
> file at `JAMGATE_STORE` — but `import` is what merges into an existing server store safely).

## Bring your memory with you

If you've been using Claude or ChatGPT for a while, they already know things about you, and
starting from an empty file is the annoying part of trying anything new.
`jamgate import --from <vendor>` takes the memory list you copy out of either one and replays
it through the same gate a live save goes through, so duplicates and junk don't come along
with it.

```bash
# Claude — a memory list you saved from Settings → Capabilities → "View and edit your memory"
jamgate import --from claude ~/Downloads/claude-memory.md

# ChatGPT — the list copied from Settings → Personalization → Memory → "Manage memories"
jamgate import --from chatgpt ~/Downloads/chatgpt-memory.txt

# Point it at the export .zip or the extracted folder — it finds the memory file inside
jamgate import --from chatgpt ~/Downloads/chatgpt-export.zip

# Always look first. Nothing is written on a dry run.
jamgate import --from claude ~/Downloads/claude-memory.md --dry-run
```

### How to get your export

Honest status, checked July 2026: **neither vendor's bulk account data export contains your
memory entries.** Both keep them in the app's own memory settings, and both document a
copy-out-the-text path. So the file you feed Jamgate is a text/markdown list, one memory per line:

| Product | Where your memories are | What to do |
| --- | --- | --- |
| **Claude** | Settings → Capabilities → **"View and edit your memory"** | Copy the list (or ask Claude: *"Write out your memories of me verbatim, exactly as they appear in your memory"*) into a `.md`/`.txt` file. Anthropic's own memory-transfer format is `[date saved, if available] - memory content` — which is what the parser expects. |
| **ChatGPT** | Settings → Personalization → Memory → **"Manage memories"** | Select the list and copy it into a `.md`/`.txt` file. A trailing `(saved 2026-01-09)` is understood. |

Dates are optional. Bullets (`-`, `*`, `1.`), markdown headings, horizontal rules and code fences
are handled. If a future export *does* ship structured memory JSON, it reads that too —
best-effort, looking for entries under memory-ish keys — and it accepts the `.zip` or the extracted
folder directly and pick the memory-shaped file out of it.

### What it reads, and what it deliberately doesn't

- ✅ **Curated memory / profile entries only** — the list you reviewed and kept in the source app.
- ❌ **It never mines your conversation logs.** `conversations.json`, `chat.html`,
  `message_feedback.json` and friends are recognized by name, skipped, and reported as skipped.
  Inferring facts about you from raw chat history is exactly the low-consent behavior this project
  exists to push back on. If the export contains nothing but chat logs, the import fails with a
  message telling you where your memories actually live.
- ❌ **It never fetches anything from a vendor account.** You download your own export, yourself.
  Jamgate reads a local file and nothing else.

### What happens to each entry

Every parsed line becomes a memory and goes **through the gate**, never blind-appended:

- **source `user-confirmed`** — you curated these in the source product. Not `user-explicit`
  (you didn't dictate them to Jamgate), not `agent-inferred` (they aren't a guess by this tool).
- **type inferred conservatively** — `preference` or `identity` only when the wording is obvious;
  otherwise left **untyped**. A wrong type is worse than no type.
- **original dates preserved** when the line carries one, so time-aware supersession orders your
  history correctly. Undated entries are stamped at import time.
- **provenance recorded** as `import:claude.ai` / `import:chatgpt`, so you can always see where a
  memory came from.
- **the gate decides** — exact duplicates are skipped, a newer fact about the same subject
  supersedes the older one, contradictions with more-trusted memories are flagged instead of
  silently applied, and near-duplicates are surfaced for you.

Because a hand-pasted file can contain stray prose (a footer, a stray note), every non-empty line
is a *candidate*. Run `--dry-run` first — it prints exactly what would land. See
[DECISIONS D-035](./DECISIONS.md).

## Deploy your own (no terminal needed)

Want one shared memory across your **phone, browser, and laptop** but don't want to run a
server? Click a button, log into a hosting platform, and you get **your own** Jamgate instance
with its own URL and token — no terminal, no server knowledge. Same gate, same store as the
local install; only the transport is over the network (this is [Remote mode](#remote-mode-self-hosted),
set up for you).

**What you should know first (honest version):**

- **You pay the platform directly. I host nothing.** A tiny always-on instance with a small
  persistent disk was roughly **$5–7/month** on Railway or Render when I last checked in August
  2026, and platform pricing moves — check theirs, not mine. That bill is between you and
  the platform; Jamgate takes no cut and runs no cloud.
- **Your instance, your data.** The memory store lives on a disk *in your account* on *your*
  platform. Jamgate never sees it, never proxies it, has no telemetry. A deploy button is
  convenience, not hosting — see [DECISIONS D-031](./DECISIONS.md).
- **Whoever holds the token holds the memory.** The deploy generates a strong bearer token for
  you. Treat it like a password. There are no per-user accounts (one instance = one person; see
  [Honest limits](#remote-mode-limits)).

### Deploy to Render (works today)

[![Deploy to Render](https://render.com/images/deploy-to-render-button.svg)](https://render.com/deploy?repo=https://github.com/amirj4m/jamgate)

The button reads [`render.yaml`](./render.yaml) straight from this repo: it builds the image from
the [`Dockerfile`](./Dockerfile), **generates a random `JAMGATE_TOKEN` for you**, and attaches a
1 GB persistent disk at `/data` for your memory. Render provisions a paid `starter` instance
(a disk needs one). After it goes live, read your token under **Environment**, and your URL is
the service URL with `/mcp` appended (e.g. `https://jamgate-xxxx.onrender.com/mcp`).

### Deploy on Railway

[![Deploy on Railway](https://railway.com/button.svg)](https://railway.com/deploy/Nb49HE)

The button deploys the published template: it builds the image from the [`Dockerfile`](./Dockerfile)
(pinned via [`railway.json`](./railway.json) with the `/healthz` check), **generates a random
`JAMGATE_TOKEN` for you**, and attaches a persistent volume at `/data` for your memory. After it
goes live, read your token under **Variables**, and your URL is the service domain with `/mcp`
appended (e.g. `https://jamgate-xxxx.up.railway.app/mcp`).

### Get your URL and token, then connect your devices

Once the deploy is live you have two things: a **URL** ending in `/mcp` and a **token** (from the
platform's environment/variables tab). Connect each device to the same instance so they share one
memory:

- **Desktops (Claude Code, Cursor, Windsurf, Gemini CLI, VS Code, Cline, Roo Code, OpenCode,
  Zed) — one command:**

  ```bash
  npx jamgate setup --remote https://your-instance/mcp --token <your-token>
  ```

  This wires every detected client on that machine to your instance (Streamable HTTP clients
  only; others — e.g. Claude Desktop — are skipped with a reason).

- **Phone (Claude app) and claude.ai in a browser:** Settings → **Connectors** → *Add custom
  connector* → URL `https://your-instance/mcp`, and provide the bearer token when asked. The same
  three tools (`save_memory`, `recall_memory`, `forget_memory`) then work from your phone.

Save on your phone, recall on your laptop — one memory, everywhere. For the full server-owner
path (your own VPS, systemd + Caddy), keep reading.

## Remote mode (self-hosted)

By default Jamgate runs **locally over stdio** — one process per agent, on your machine, no
network. That's the right model for a single computer. But you are one person with agents in
several places at once: the Claude app on your **phone**, claude.ai in a **browser**, Claude
Code on a **laptop**. stdio can't be their shared brain — each would get its own local process
and its own memory.

**Remote mode** is the answer: run **one** Jamgate instance on a server you control, put it
behind HTTPS, and point every agent at the same URL. Now they share **one** memory of you — save
on your phone, recall on your laptop. It's the same gate and the same store, just reachable over
the network. It stays **opt-in**; stdio remains the default and the local-first promise is
unchanged. Whether it's your own memory or a whole team's, the rule is one instance per person
(see [Honest limits](#remote-mode-limits)).

### Run it

```bash
# A strong token is REQUIRED — the server refuses to start without one.
export JAMGATE_TOKEN=$(openssl rand -hex 32)
jamgate --http                 # listens on 127.0.0.1:8420/mcp
# or: jamgate --http --port 9000     (or JAMGATE_HTTP=1 JAMGATE_PORT=9000)
```

The MCP endpoint is `/mcp`. Every request must carry `Authorization: Bearer <token>`; anything
else gets a `401`. In remote mode Jamgate also serves the standard **MCP OAuth flow** (on by
default) so it can be added to claude.ai and the Claude mobile app — see
[Adding to claude.ai](#adding-to-claudeai-mcp-oauth).

### Security model

- **Bearer token.** One shared secret in `JAMGATE_TOKEN` guards every request, compared in
  constant time so it can't be recovered from response timing. Generate it with
  `openssl rand -hex 32`, keep it out of shell history, and rotate it by restarting with a new
  value.
- **TLS is terminated by a reverse proxy, not by Jamgate.** Jamgate speaks plain HTTP and binds
  to `127.0.0.1` by default, so it is never directly exposed. Put **caddy** or **nginx** in
  front to terminate HTTPS and forward to it locally. A bearer token over plain HTTP on the open
  internet is a leaked token — **always** run it behind TLS.
- **Your server, your data.** The store is still a flat file on a disk you own. No Jamgate cloud,
  no third party, no telemetry. "Self-hosted" means exactly that.
- **OAuth without an identity provider.** For clients that require OAuth (claude.ai, the Claude
  app), your instance is its own authorization server — your `JAMGATE_TOKEN` is still the only
  credential, PKCE is enforced, and issued tokens are stored hashed and revocable. Details in
  [Adding to claude.ai](#adding-to-claudeai-mcp-oauth).

### REST API (for app backends)

MCP is the right protocol for agents, but an ordinary app backend just wants plain HTTP. In
remote mode Jamgate also serves a small REST API on the **same port**, behind the **same bearer
token** — so a mobile app or a script can save and recall without speaking JSON-RPC:

```bash
BASE=https://memory.example.com/v1/memory
AUTH="Authorization: Bearer $JAMGATE_TOKEN"

# Save (optionally into a namespace — see "Namespaces" above)
curl -sX POST "$BASE" -H "$AUTH" -H 'Content-Type: application/json' \
  -d '{"text":"the aorist tense expresses a completed action","scope":"amir/greek","type":"project"}'

# Recall within a scope
curl -s "$BASE?query=aorist&scope=amir/greek" -H "$AUTH"

# Forget by id, within a scope
curl -sX DELETE "$BASE/<id>?scope=amir/greek" -H "$AUTH"
```

| Method & path | Body / query | Returns |
| --- | --- | --- |
| `POST /v1/memory` | `{text, scope?, type?, subject?, source?}` (`content`/`memory` accepted as aliases of `text`) | `201` with `{action, memory, …}` when a record lands; `200` with the gate's `action` when it deliberately stores nothing (`duplicate`/`conflict`/`possible_duplicate`/`rejected`) |
| `GET /v1/memory` | `?query=&scope=&limit=` | `200` with `{memories: […]}` |
| `DELETE /v1/memory/:id` | `?scope=` | `200 {ok:true,id}`, `404` not found, `409` ambiguous prefix |

Every REST save goes through the **exact same gate** as the MCP tool (dedup, supersession,
conflict guard, credential refusal), per scope. A missing/wrong token is a `401`; a malformed
body is a `400`. The MCP endpoint (`/mcp`) and the OAuth flow are unaffected — REST is purely
additive.

### Deploy: systemd + Caddy

A `systemd` unit to keep Jamgate running (fill in your user and a real token — ideally load the
token from an `EnvironmentFile` with `600` permissions rather than inlining it):

```ini
# /etc/systemd/system/jamgate.service
[Unit]
Description=Jamgate MCP memory (remote mode)
After=network.target

[Service]
# Load JAMGATE_TOKEN=... (and any JAMGATE_* overrides) from a root-only file:
EnvironmentFile=/etc/jamgate.env
Environment=JAMGATE_HTTP=1
Environment=JAMGATE_PORT=8420
Environment=JAMGATE_STORE=/var/lib/jamgate/memory.json
ExecStart=/usr/bin/npx jamgate
User=jamgate
Restart=on-failure

[Install]
WantedBy=multi-user.target
```

```bash
echo "JAMGATE_TOKEN=$(openssl rand -hex 32)" | sudo tee /etc/jamgate.env >/dev/null
sudo chmod 600 /etc/jamgate.env
sudo systemctl enable --now jamgate
```

**Caddy** — automatic HTTPS, two lines of real config:

```caddyfile
memory.example.com {
    reverse_proxy 127.0.0.1:8420
}
```

**nginx** — equivalent, with TLS certs managed by certbot. Note that nginx, unlike Caddy's
`reverse_proxy`, forwards **only the paths you name**: every Jamgate surface needs its own
`location`, and one you forget returns nginx's own 404 without the request ever reaching
Jamgate.

```nginx
server {
    listen 443 ssl;
    server_name memory.example.com;

    ssl_certificate     /etc/letsencrypt/live/memory.example.com/fullchain.pem;
    ssl_certificate_key /etc/letsencrypt/live/memory.example.com/privkey.pem;

    location /mcp {
        proxy_pass         http://127.0.0.1:8420/mcp;
        proxy_http_version 1.1;
        proxy_set_header   Connection "";        # keep-alive for SSE streaming
        proxy_buffering    off;                  # don't buffer the event stream
        proxy_read_timeout 3600s;
    }

    # REST API (0.10.0). REQUIRED if you use it — without this block `/v1/memory` is a
    # 404 from nginx, not a 401 from Jamgate, and every REST client silently sees "no
    # such endpoint" instead of "you need a token".
    location /v1/ {
        proxy_pass         http://127.0.0.1:8420;
        proxy_http_version 1.1;
        proxy_set_header   Host $host;
        proxy_set_header   Authorization $http_authorization;
    }

    # MCP OAuth (needed for claude.ai and the Claude mobile app).
    location /.well-known/ { proxy_pass http://127.0.0.1:8420; }
    location /authorize    { proxy_pass http://127.0.0.1:8420; }
    location /token        { proxy_pass http://127.0.0.1:8420; }
    location /register     { proxy_pass http://127.0.0.1:8420; }

    # Liveness probe (unauthenticated by design; exposes only status + version).
    location /healthz { proxy_pass http://127.0.0.1:8420/healthz; }
}
```

**Verify each surface actually reaches Jamgate** after any proxy change — an unauthenticated
request must come back `401` from Jamgate, never `404` from the proxy:

```bash
curl -si https://memory.example.com/v1/memory | head -1   # expect: HTTP/2 401
curl -s  https://memory.example.com/healthz               # expect: {"status":"ok","version":"…"}
```

### Connect your agents

Point every agent at `https://your-domain/mcp` with the token.

**Claude app (iOS / Android / desktop) and claude.ai** — Settings → Connectors → *Add custom
connector* → paste the URL `https://your-domain/mcp` and click through. These clients only speak
the standard **MCP OAuth flow**, so instead of pasting a token into a config field, a Jamgate
page opens in your browser and asks: *"This is your Jamgate instance. Enter your instance token
to authorize this client."* Paste your `JAMGATE_TOKEN` **once**, and Claude is connected — it
remembers the authorization, so you won't be asked again for that client. Once connected, the
same three tools (`save_memory`, `recall_memory`, `forget_memory`) are available from your phone
and browser. See [Adding to claude.ai](#adding-to-claudeai-mcp-oauth) below for what happens under
the hood.

**Claude Code** — add it as an HTTP MCP server:

```bash
claude mcp add --transport http jamgate https://your-domain/mcp \
  --header "Authorization: Bearer <token>"
```

**Any MCP client** that speaks Streamable HTTP works the same way: URL `https://your-domain/mcp`,
header `Authorization: Bearer <token>`.

### Adding to claude.ai (MCP OAuth)

claude.ai and the Claude mobile app cannot take a static token in a config field — they only
support the [MCP authorization flow](https://modelcontextprotocol.io/specification/2025-06-18/basic/authorization)
(OAuth 2.1 + PKCE). Jamgate implements that flow itself in remote mode, so **no external identity
provider is involved** — your instance *is* the authorization server, and your `JAMGATE_TOKEN` is
the one credential. It's **on by default** whenever you run `--http` (disable with
`JAMGATE_OAUTH=off` if you only ever use Claude Code with a static header).

What you do:

1. In claude.ai (or the app): Settings → Connectors → *Add custom connector* → URL
   `https://your-domain/mcp`.
2. Claude discovers the flow, registers itself, and opens a Jamgate page in your browser.
3. The page asks for your **instance token** — paste your `JAMGATE_TOKEN` and submit. That's the
   only thing it ever asks for, and only once per client.
4. You're connected. `save_memory` / `recall_memory` / `forget_memory` now work from that client.

What happens under the hood (all served by your instance, same origin, no third party):

| Endpoint | Spec | Purpose |
| --- | --- | --- |
| `GET /.well-known/oauth-protected-resource` | [RFC 9728](https://datatracker.ietf.org/doc/html/rfc9728) | Tells the client where the authorization server is. A `401` from `/mcp` also carries a `WWW-Authenticate` header pointing here. |
| `GET /.well-known/oauth-authorization-server` | [RFC 8414](https://datatracker.ietf.org/doc/html/rfc8414) | Advertises the endpoints below; PKCE **S256** required. |
| `POST /register` | [RFC 7591](https://datatracker.ietf.org/doc/html/rfc7591) | Dynamic client registration — the client gets a `client_id`. |
| `GET`/`POST /authorize` | OAuth 2.1 | The consent page that asks for your instance token, then issues a single-use, PKCE-bound authorization code. |
| `POST /token` | OAuth 2.1 | Exchanges the code (+ PKCE verifier) for a long-lived access token (and a refresh token). |

Security: PKCE (S256) is mandatory, redirect URIs are matched exactly (no open redirect),
authorization codes are single-use and expire in ≤60s, and access/refresh tokens are stored
**hashed** in `~/.jamgate/oauth.json` (revoke one by deleting its entry) with the same atomic,
locked writes as the memory store. The `/mcp` endpoint accepts **either** an issued OAuth access
token **or** the static `JAMGATE_TOKEN`, so existing Claude Code connections keep working
unchanged.

### Remote mode limits

These are on top of the [general limits](#honest-limits) above.

- **Whoever holds the token holds the memory.** There are no per-user accounts; the token *is*
  the authentication. Treat it like a password: strong, secret, rotated on suspicion.
- **One instance is one human.** There is no multi-user tenancy, no per-identity isolation, no
  access control. That was a scope decision, and it keeps the security surface down to one
  secret and one store, but if three people each want a memory you run three instances.
- **Concurrency is single-process.** Several agents hitting one instance at once is safe —
  writes take a lock and re-read before writing. That holds for one process on one host. It is
  not a distributed store and will not survive being run twice against the same file.
- **No TLS in the box.** Skip the reverse proxy and you are sending a bearer token in the
  clear. Don't.
- **One memory is one fact, up to 32 KB.** Bigger saves are refused rather than truncated. If
  you want a document remembered, save the conclusion.

## How it compares

There are no benchmark numbers here. This category has had two of them retracted in public and
I am not adding a third from a project with one user.

The column that should worry me most is the last one. Letta benchmarked plain markdown files
with `grep` and semantic search against Mem0 on LoCoMo and the files won — **74.0% versus
68.5%** with GPT-4o mini
([their write-up](https://www.letta.com/blog/benchmarking-ai-agent-memory)). That is somebody
else's benchmark of somebody else's system, and Jamgate has never been run on LoCoMo, so I
cannot tell you where it would land. But the honest reading is that a directory of text files
and a twenty-year-old command-line tool is a serious baseline, and any memory product that
cannot say why it beats that baseline probably doesn't.

| | **Jamgate** | **Mem0 / OpenMemory** | **Zep / Graphiti** | **Plain files + `grep`** |
| --- | --- | --- | --- | --- |
| Core model | Rule-based gate in front of a flat file | LLM-extracted memory layer | Temporal knowledge graph | A directory of text |
| Where memory lives | A JSON file on your machine | Hosted platform or self-hosted store | Graph server (self-hosted or cloud) | Files on your machine |
| Gate before write | Core design | Partial (dedup/update) | Partial | **None** |
| Duplicates | Exact + optional semantic | Yes | Yes | **Pile up forever** |
| Superseding an outdated fact | By `subject`, automatically | Partial | Yes, temporally | **You edit the file** |
| Source-trust hierarchy | Yes | Not that I can find | Not that I can find | **No such concept** |
| Expiry of volatile state | By type, automatic | Partial | Yes | **Never** |
| LLM calls of its own | None | Required | Required | **None** |
| Dependencies / infra | 1 runtime dep, no server | SDK + service/DB | Graph DB + service | **Zero. You have it already** |
| **Retrieval quality** | **Weak.** Fuzzy lexical + optional local embeddings; 10/17 top-1 on my own store | Real vector retrieval and reranking, tuned over many deployments | Graph traversal plus vector search | **Beat Mem0 on LoCoMo** (74.0 vs 68.5) |
| **Understands what a memory means** | **No.** Regexes, subject matching, cosine thresholds | Yes — LLM extraction is the whole design | Yes — entity and relationship extraction | **No** |
| **Entity / relationship reasoning** | **None.** Flat records with a `subject` string | Some | This is what it is for | **None** |
| **Scale** | **Measured to 10,000 records; recall slows past ~2,000** (758 ms at 10k). One file, read whole, no index | Production deployments | Production deployments | **Millions of lines, fine** |
| **Multi-user / teams** | **No.** One instance, one person, one token | Yes | Yes | **Whatever your filesystem does** |
| **Language support** | Lexical recall in any script; semantic is **English-only** | Multilingual models | Multilingual models | **Any bytes at all** |
| **SDKs** | MCP and a small REST API | Python, TS, and more | Python, TS, and more | **Every language ever written** |
| **Maturity** | **One developer, one user; see the [releases](https://github.com/amirj4m/jamgate/releases)** | Funded team, wide adoption | Funded team, wide adoption | **Older than all of us** |
| Best for | One person's cross-agent memory, kept small and current, on their own disk | Application-scale memory with real retrieval | Relationship and temporal reasoning | Almost certainly your first thing to try |

Read that last column honestly: `grep` beats Jamgate on retrieval, scale, language support, and
every kind of maturity, and it costs nothing because you already have it. What it has no
concept of is *writing* — every duplicate, every contradiction and every stale fact stays in
your files until you go and edit them yourself. That is the entire bet of this project: that
for a memory several agents write to unattended, the write side is where the work is. If you
are happy curating the files yourself, curate the files yourself. You will probably get better
retrieval than I can give you.

The Jamgate column is checked by the test suite and by the measurements in
[`DECISIONS.md`](./DECISIONS.md). The other two are read from those projects' public
documentation as of **August 2026** and describe default behaviour, not the ceiling of what
they can be configured to do. If a row is wrong, open an issue and I will fix it — including
the ones that are unflattering to them.

Short version: if you want the best retrieval, use Mem0. If your memory is really a graph of
people and events, use Zep. Jamgate is worth a look if what you want is one small memory of
yourself that several agents share, on a disk you own, and you care more about it staying
clean than about it being clever.

## Privacy

Your memories are never sent anywhere by Jamgate. There is no outbound request carrying your
data, no telemetry, no accounts and no keys. Jamgate has no provider of its own to call. The
store, the gate and the embedding model all run on your machine.

Two things do touch the network, both of them downloads and neither carrying your text: `npx`
fetching the package from npm, and — only if you installed the optional semantic package — the
embedding model's first-run download from Hugging Face (about 90 MB, then cached). Both stop
after install.

The thin classifier is the one place any of your text moves, and only on a client that
implements MCP sampling. When it fires, the gate sends one question back down the MCP
connection it is already serving, and your agent answers it with the model it was already
using. Jamgate still calls nobody. What travels is only the text of the save being judged,
never another memory, never the store, never a recall result, and it goes to the model that
just wrote that text in the same session, so it cannot disclose anything your client did not
already have. On a client without sampling it never happens at all, which today is most of
them. If you would rather it never happened anywhere, set `JAMGATE_CLASSIFIER=off`.

There is also a local decision log. Every gate verdict (saved, duplicate, superseded,
conflict, possible_duplicate, rejected), plus the classifier's answer on the decisions where
one was consulted, is appended to a size-capped JSONL file that rotates on its own and never
leaves the machine. I keep it because it is the corpus the classifier is measured against, and
a future local classifier would need real examples to be any good. It lives beside the store —
`gate.log` in the same directory as `JAMGATE_STORE`, or `~/.jamgate/gate.log`.
`JAMGATE_GATE_LOG` overrides the path and `JAMGATE_GATE_LOG=off` turns it off. It holds the
memory text, so if that bothers you, turn it off. (It follows the store rather than the home
directory so it stays writable under a hardened systemd unit with `ProtectHome=true`; see
D-037.)

## Status

I use this daily, it holds my real memory, and it has not lost a record. That is the strongest
claim I can make honestly. It is not battle-tested, because there has only ever been one
battle.

What works today: the gate itself (rule pre-filter, credential refusal, exact dedup,
time-aware supersession, the source-trust conflict guard), atomic durable writes with locking
and schema migration, fuzzy recall in any script with optional local embeddings on top, the
`setup` wizard for ten clients, and `import --from claude|chatgpt` for moving your memory off
another product. Optional and less exercised: remote mode over HTTP with a bearer token and
MCP OAuth, a small REST API on the same port, and namespaces. Those last three work and are
tested, but I am the only person who has ever pointed anything at them — the local stdio path
is the one that gets used every day.

644 tests on Node 20 and 22, run against a real MCP handshake on both transports. The full
history is in [`CHANGELOG.md`](./CHANGELOG.md), and every non-obvious decision, including the
ones I got wrong and reversed, is written up in [`DECISIONS.md`](./DECISIONS.md).

The thin classifier for ambiguous cases is now built and measured, but read the row in the
table above before you count on it: it is inert on every client that does not implement MCP
sampling, which today is nearly all of them.

Next: better recall ranking, a `reindex` command, and a client that can actually answer a
sampling request. MIT, and I am not trying to make money from it.

## Development

```bash
npm install
npm run build   # compile TypeScript to dist/
npm test        # compile and run the test suite (built-in node:test, no extra deps)
```

CI runs the build and tests on Node 20.x and 22.x for every push and pull request.

## Contributing

The most useful thing you can do right now is install it and tell me what broke, especially
on macOS or Windows, which I have never run. After that: recall ranking, which is the part
I'm least happy with.

[`AGENTS.md`](./AGENTS.md) gets you oriented and [`RULES.md`](./RULES.md) has the detail.
Both are written for an AI agent as much as for a person, since most of this was built with
one.

## License

[MIT](./LICENSE)