# th-memory-mcp [Health: Active]

**Category:** 🗄️ Databases  
**Repository:** https://github.com/worakorn-prince/th-memory-mcp  
**GitHub Stars:** 3  
**npm Downloads (last month):** 2555  
**Views:** 0  
**Installs:** 0  
**Upvotes:** 0  
**Directory Page:** https://allmcps.com/mcp/th-memory-mcp

## Description
Adaptive Memory MCP server - SQLite-backed memory for OpenCode

## Tools
Capabilities this server exposes over MCP:

- **remember** — upsert preference (category+key) — re-saving the same key increases confidence by 0.1 (cap 1.0)
- **recall** — search preferences + lessons (FTS5) + recent matching interactions. Use before starting a new task
- **get_profile** — user profile overview: profile sections + top preferences + 5 most recent lessons
- **save_lesson** — record a lesson learned from a correction (situation / mistake / correction)
- **search_history** — search past user prompts by keyword (200-char snippets per row)
- **forget** — delete one memory row (preference/lesson/interaction) by id (+type prevents cross-table id clash)
- **memory_stats** — memory statistics: counts by kind, DB size, oldest/newest interaction, profile sections
- **get_recent_interactions** — list recent raw interactions (filter by kind) — feedstock for Smart Distill
- **export_memory** — export memory to JSON under `data/exports/` only (filename auto-sanitized)
- **get_context** — assemble relevant memories for the current task via hybrid retrieval (+ optional graph expansion) with token budgeting
- **consolidate** — cluster similar memories via embedding similarity; optionally create derived/consolidated memories linked via `derived_from
- **link_memory** — create a typed relationship between two memories in the graph (supports/contradicts/supersedes/derived_from/related_to/caused_by/depends_on)
- **merge_memory** — merge a duplicate/near-duplicate into a canonical memory (source becomes superseded, provenance in `metadata.merged_from`)
- **update_memory** — update mutable fields in place, or create a superseding memory when `content` changes (set `supersede=false` to edit in place)
- **import_memory** — import memories from JSON (validates type, dedupes against existing, never overwrites blindly); dry-run by default, `apply=true` to insert
- **extract_memories** — scan recent captured interactions for memory-intent phrases and propose memory candidates (deterministic, no LLM); dry-run by default, `apply=true` to create (source=captured)

## Claude Desktop Quick Installation
Install path detected from listing signals. Uses `npx` (confidence: high):

```json
"mcpServers": {
  "th-memory-mcp": {
    "command": "npx",
    "args": ["-y","th-memory-mcp"]
  }
}
```

## Documentation & README

# th-memory-mcp

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**Status:** v2.2.8 — a temporal, conflict-aware, hybrid-retrieval memory engine. 16 MCP tools, 25 passing test suites. Non-destructive schema migration from v1 (all v1 data preserved). New in v2.2: lifecycle states, temporal validity, conflict/dedup resolution with USER/SESSION/PROJECT/GLOBAL scope, hybrid FTS+vector retrieval (RRF), memory graph, `get_context` assembly, periodic consolidation, and `link_memory` / `merge_memory` / `update_memory` / `import_memory` / `extract_memories`. New in v2.2.3: scope-enforced retrieval, graph scope isolation, export/import round-trip, hardened import path (realpath), strict import validation, N+1 query elimination, cold/ablation benchmark, and `MEMORY_RETRIEVAL_MODE` switch. New in v2.2.7: synced secret filter between Claude hook and capture-core (6-pattern redact instead of line-drop), fixed `err()` to return `isError:true` per MCP spec, fixed backup rotation (backup only when migrations pending + prune to 5 files), and added hook error logging for SessionEnd distill. New in v2.2.8: fixed scope contamination 0.75→0 (critical) and conflict false 0→1 (GLOBAL leak), fixed graph hop1 0.52→1.0 via includeGraph, and rescaled benchmark profiles to 5K/20K/100K/500K/1M (pre-commit now quick 5K + normal 20K only).

## Requirements

- **Node.js >= 20** — the server uses Node-only APIs (the `better-sqlite3` native build and `import.meta.url` resolution) and the MCP SDK requires a modern runtime. CI tests on Node 20.x and 22.x.
- **npm** — to install dependencies and run the build/test scripts (`npm install`, `npm run build`, `npm test`).
- **OpenCode** — the host that loads this MCP server and the auto-capture plugin. Any build supporting MCP over stdio + plugins works; the plugin runs on OpenCode's bundled Bun runtime.
- **OS: Windows / macOS / Linux** — the server is cross-platform (Node). The auto-capture plugin runs wherever OpenCode's Bun runtime runs. Windows note: `MEMORY_DB_PATH` is easiest to set with `setx`; on macOS/Linux use `export` in your shell profile.

No external services, accounts, or API keys are required — everything lives in a single local SQLite file.

## Quick Start

**Fastest path:** after cloning, run `npm run quickstart` — it builds, wires `opencode.json`, deploys the plugin, and sets `MEMORY_DB_PATH` for you in one command. The steps below show exactly what it does (use them if you prefer manual control).

**Install via npm (alternative):** install the server globally with `npm install -g th-memory-mcp` (or run it on demand with `npx th-memory-mcp`), then point the `mcp` `command` in `opencode.json` to `th-memory-mcp` instead of the built `dist/index.js`. The auto-capture plugin still comes from this repo (copy `src/plugin/learning-capture.ts` as described in step 4 below).

```bash
# 1. Clone and build
git clone https://github.com/worakorn-prince/th-memory-mcp.git
cd th-memory-mcp
npm install
npm run build

# 2. Share one DB between the server and the plugin
#    Windows (PowerShell):
setx MEMORY_DB_PATH "$PWD/data/memory.db"
#    macOS / Linux (add to your shell profile, e.g. ~/.zshrc):
# export MEMORY_DB_PATH="$PWD/data/memory.db"
```

3. Merge this into your `~/.config/opencode/opencode.json` (replace `<REPO>` with the absolute clone path):

```json
{
  "instructions": ["<REPO>/AGENTS.memory.example.md"],
  "mcp": {
    "memory": {
      "type": "local",
      "command": ["node", "<REPO>/dist/index.js"],
      "enabled": true,
      "environment": { "MEMORY_DB_PATH": "<REPO>/data/memory.db" }
    }
  }
}
```

4. (Optional) Auto-capture: copy `src/plugin/learning-capture.ts` → `~/.config/opencode/plugins/`
5. **Restart OpenCode**
6. Try it: *"Remember that I prefer pnpm"* → new session → *"What package manager do I prefer?"*

## Architecture

```
OpenCode ──┬─ Plugin learning-capture (Bun)  ── auto-captures prompts/tool/error into DB
            │                                   └─ injects profile back into context on compaction
             └─ MCP th-memory-mcp (Node.js stdio)  ── 16 tools read/write the same SQLite DB
                                                      ▲
                               Global instructions (memory-protocol.md) teach the AI to use the tools
```

See [ARCHITECTURE_v2.md](https://github.com/worakorn-prince/th-memory-mcp/blob/HEAD/ARCHITECTURE_v2.md) for the full architecture spec.

## Why th-memory-mcp?

LLMs don't remember you between sessions — every new chat starts blank. th-memory-mcp gives your AI a private, local long-term memory:

- **Context-based learning, not fine-tuning** — it captures your preferences, corrections, and habits, then recalls them into context next time. Same mechanism as the memory features of leading AI products, without sending any data off your machine.
- **100% local & private** — a single SQLite file, no cloud, no external API. Secrets are filtered before anything is stored.
- **Low overhead** — each tool call is capped (latency < 10 ms, bounded output size) and the AI only queries memory when it's actually useful, so it never bloats your context.
- **Resilient** — every tool degrades gracefully; if the DB is unavailable the AI keeps working instead of crashing.
- **Open & extensible** — MIT licensed, 16 documented tools, a rule-based distill, and an auto-capture plugin you can adapt.

## Works with other harnesses

th-memory-mcp is a standard MCP server, so the 9 tools run anywhere MCP-over-stdio
is supported. Full **auto-capture** (background prompt/tool/error capture + profile
injection) needs a hook runtime — OpenCode has it built in; Claude Code gets it via
our hooks bridge; Codex and Cursor use the tools manually (no hook runtime yet).

| Feature | OpenCode | Claude Code | Qwen Code | Codex | Cursor |
|---|---|---|---|---|---|
| 16 MCP tools | ✅ | ✅ | ✅ | ✅ | ✅ |
| Auto-capture (background) | ✅ plugin | ✅ [hooks](https://github.com/worakorn-prince/th-memory-mcp/blob/HEAD/CLAUDE_CODE_HOOKS.md) | ⚠️ adapter | ❌ manual | ❌ Rules |
| Profile injection | ✅ compaction | ✅ UserPromptSubmit | ❌ `get_profile` | ❌ `get_profile` | ❌ `get_profile` |
| Lexical fuzzy matching | ✅ (v2.0) | ✅ (v2.0) | ✅ (v2.0) | ✅ (v2.0) | ✅ (v2.0) |

- **Claude Code:** see [CLAUDE_CODE_HOOKS.md](https://github.com/worakorn-prince/th-memory-mcp/blob/HEAD/CLAUDE_CODE_HOOKS.md) — drop-in hooks replicate the OpenCode plugin (capture + profile injection on `UserPromptSubmit`/`PreCompact`, rule-based distill on `SessionEnd`).
- **Qwen Code:** see [QWEN_SETUP.md](https://github.com/worakorn-prince/th-memory-mcp/blob/HEAD/QWEN_SETUP.md) — MCP works fully; hooks use the Gemini-CLI schema so auto-capture needs a small adapter.
- **Codex:** see [CODEX_SETUP.md](https://github.com/worakorn-prince/th-memory-mcp/blob/HEAD/CODEX_SETUP.md)
- **Cursor:** see [CURSOR_SETUP.md](https://github.com/worakorn-prince/th-memory-mcp/blob/HEAD/CURSOR_SETUP.md)

All harnesses share one SQLite file via `MEMORY_DB_PATH`, so memory captured
anywhere is readable everywhere.

## Highlights

- **Structured memory** — preferences with confidence scoring plus dedicated
  `lesson` records (situation → mistake → correction) for capturing corrections,
  not just flat facts.
- **Lifecycle & temporal** — every memory has a lifecycle state
  (active/stale/superseded/archived), confidence/importance/salience scoring,
  per-type decay, and validity intervals so the AI can reason about
  point-in-time truth and supersession chains.
- **Conflict-aware** — duplicate detection, contradiction detection, and
  update/supersession resolution preserve both sides of ambiguous evidence
  instead of silently overwriting.
- **Hybrid retrieval** — `get_context` blends FTS5 keyword search with a
  dependency-free lexical fuzzy matching (hashed n-gram similarity, 512-dim FNV-1a) (RRF fusion + scoring), then assembles
  a token-budgeted context with optional memory-graph expansion.
- **Consolidation** — periodic clustering of similar memories into derived
  memories with full provenance (`derived_from` links).
- **First-class Thai / i18n** — Thai-aware tokenization in distill; the AI
  accepts Thai and English interchangeably.
- **Private by default** — a single local SQLite file, no cloud, no API keys,
  with secret lines (`api_key=`, `password:`, `token`) filtered before storage.
- **Cross-harness** — runs on OpenCode, Claude Code, Codex, and Cursor sharing
  one DB; auto-capture + profile injection via OpenCode plugin or Claude hooks.
- **Lightweight & resilient** — Node + `better-sqlite3`, no extra native
  extensions; every tool degrades gracefully so the AI keeps working if the DB
  is unavailable.

## Scripts

| Command | Description |
|---------|-------------|
| `npm run build` | compile TypeScript → `dist/` |
| `npm start` | run the MCP server (stdio) from `dist/index.js` |
| `npm run distill` | rule-based distill: interactions → profile sections + prune old data (env `RETENTION_DAYS` default 30) |
| `npm test` | full suite: capture, distill, lifecycle, temporal, conflict, retrieval, graph, context, consolidation, benchmark, security, tools_v21, smoke, e2e_transport, retrieval_benchmark, recall_regression, scope, profile, entity_extraction, conflict_benchmark, security_regression, export_import_roundtrip |
| `node test/capture.test.mjs` | test capture-core (filter secrets, dedupe, truncate, insert SQL) |
| `node test/distill.test.mjs` | test distill-core (Thai tokenize, stats, profile sections, prune) |
| `node test/lifecycle.test.mjs` | test lifecycle engine (states, decay, supersession) |
| `node test/temporal.test.mjs` | test temporal model (validity, historical retrieval) |
| `node test/conflict.test.mjs` | test conflict & dedup resolution |
| `node test/retrieval.test.mjs` | test hybrid FTS+vector+RRF retrieval |
| `node test/graph.test.mjs` | test memory graph (entities, relations, traversal) |
| `node test/context.test.mjs` | test context assembly + token budgeting |
| `node test/consolidation.test.mjs` | test clustering + derived memories |
| `node test/benchmark.test.mjs` | latency benchmark over 300 memories |
| `node test/security.test.mjs` | injection / safety checks |
| `node test/smoke.mjs` | end-to-end smoke test over JSON-RPC (16 tools) |

## Tools (16)

| Tool | Description |
|------|-------------|
| `remember` | upsert preference (category+key) — re-saving the same key increases confidence by 0.1 (cap 1.0) |
| `recall` | search preferences + lessons (FTS5) + recent matching interactions. Use before starting a new task |
| `get_profile` | user profile overview: profile sections + top preferences + 5 most recent lessons |
| `save_lesson` | record a lesson learned from a correction (situation / mistake / correction) |
| `search_history` | search past user prompts by keyword (200-char snippets per row) |
| `forget` | delete one memory row (preference/lesson/interaction) by id (+type prevents cross-table id clash) |
| `memory_stats` | memory statistics: counts by kind, DB size, oldest/newest interaction, profile sections |
| `get_recent_interactions` | list recent raw interactions (filter by kind) — feedstock for Smart Distill |
| `export_memory` | export memory to JSON under `data/exports/` only (filename auto-sanitized) |
| `get_context` | assemble relevant memories for the current task via hybrid retrieval (+ optional graph expansion) with token budgeting |
| `consolidate` | cluster similar memories via embedding similarity; optionally create derived/consolidated memories linked via `derived_from` |
| `link_memory` | create a typed relationship between two memories in the graph (supports/contradicts/supersedes/derived_from/related_to/caused_by/depends_on) |
| `merge_memory` | merge a duplicate/near-duplicate into a canonical memory (source becomes superseded, provenance in `metadata.merged_from`) |
| `update_memory` | update mutable fields in place, or create a superseding memory when `content` changes (set `supersede=false` to edit in place) |
| `import_memory` | import memories from JSON (validates type, dedupes against existing, never overwrites blindly); dry-run by default, `apply=true` to insert |
| `extract_memories` | scan recent captured interactions for memory-intent phrases and propose memory candidates (deterministic, no LLM); dry-run by default, `apply=true` to create (source=captured) |

## Install with OpenCode

1. Merge the `mcp` section from [`opencode.example.json`](https://github.com/worakorn-prince/th-memory-mcp/blob/HEAD/opencode.example.json) into your `opencode.json` (global or project-level)
   - **Important:** set `MEMORY_DB_PATH` to the SAME database file for both the server and the plugin (the example uses `<ABSOLUTE_PATH>/th-memory-mcp/data/memory.db`), otherwise the auto-capture plugin writes to a different DB than the one the AI reads
   - How to set it (pick one):
     - define it in the mcp `environment` (see example) — covers the MCP server only
     - **or** set it as a system/user-level environment variable (e.g. `setx MEMORY_DB_PATH "D:/path/to/memory.db"` on Windows) — covers both server and plugin, since the plugin runs in the same process as OpenCode
2. Attach the global memory rules — add to `opencode.json`:
   ```json
   "instructions": ["C:/Users/<user>/.config/opencode/memory-protocol.md"]
   ```
   (example rule content is in [`AGENTS.memory.example.md`](https://github.com/worakorn-prince/th-memory-mcp/blob/HEAD/AGENTS.memory.example.md) — can be attached at project level instead)
3. (Optional) Deploy the auto-capture plugin: copy `src/plugin/learning-capture.ts` → `~/.config/opencode/plugins/learning-capture.ts`
4. **Restart OpenCode** (config loads at startup only)
5. Test: *"Remember that I prefer pnpm"* → open a new session and ask back

## Daily usage

The AI accepts both Thai and English interchangeably — you can switch languages at any time without warning.

| Example command | Tool / effect |
|-----------------|---------------|
| "Remember that..." | `remember` — save a preference |
| "Summarize memory" / "distill memory" | **Smart Distill** — AI reads `get_recent_interactions`, finds patterns, and saves insights itself |
| "How is my memory?" / "memory status" | `memory_stats` |
| "Export memory" / "backup memory" | `export_memory` |
| "Search history..." | `search_history` |
| "Forget..." | `forget` |

Long-term care: run `npm run distill` occasionally to summarize stats and prune interactions older than 30 days.

## data/ structure

```
data/
├── memory.db          # SQLite (WAL mode) — main DB (+ .db-wal, .db-shm)
└── exports/           # JSON files from export_memory (writeable only in this dir)
```

- DB path can be overridden via the `MEMORY_DB_PATH` env var
- everything in `data/` is git-ignored

## Benchmark — internal self-reported (not third-party)

> **⚠️ Internal self-reported benchmark — not third-party benchmark**
> - **internal small-N**: **180 records/30 topics** (B.retrieval: 30 topics × 5 relevant + 30 distractors = 180; full run also uses small-N storage/temporal/context subsets)
> - **single-machine self-run**: single developer machine, single OS/Node/better-sqlite3 build — not cross-machine, not independently verified
> - **not third-party benchmark**: self-reported, not independently verified; do not compare as if from an external evaluator
> - Dataset and harness are in `repro/` (commitable) and `benchmark/` (full framework, see `TH_MEMORY_MCP_BENCHMARK_SPEC.md` and `benchmark/README.md`).

**Two modes**

| Mode | Command | Data | Suites | Use case |
|------|---------|------|--------|----------|
| Normal | `npm run benchmark` | 180 records / 30 topics | retrieval | quick check (<5s) |
| Heavy | `npm run benchmark:heavy` | 600 records / 100 topics + 2k scale | all (storage/retrieval/temporal/context/performance/scalability/cold/ablation) | stress / regression |

Reproduce:

```powershell
npm run build
# Normal — quick
npm run benchmark
npm run benchmark -- --k 10
npm run benchmark -- --out repro/results

# Heavy — full framework, more data
npm run benchmark:heavy
# or custom:
node benchmark/run.mjs --suite all --topics 100 --distractors 100 --scale 2000 --out benchmark/results
```

**Viewer — compare last 3 versions (table + charts)**

```powershell
npm run benchmark:viewer
# or: npx serve . -l 3000
# open http://localhost:3000/benchmark/viewer/  or  http://localhost:3000/result/viewer.html
```

The viewer loads `benchmark/results/history.jsonl`, groups by version, takes the **latest run of the 3 most recent versions** (e.g. 2.2.2 / 2.2.3 / 2.2.4) and shows a highlighted table (1 row per version) + bar charts for `Recall@5 / MRR / NDCG@5` and `Latency p95`. Results are also saved per version in `result/v*_benchmark_result.md` and `benchmark/results/versions/<ver>/`.

Last internal run (v2.2.4, warm, same dataset — not third-party): Recall@5=0.92, Precision@5=0.92, MRR=1.00, NDCG@5=0.94 over 30 topics/180 records. See `result/v2.2.4_benchmark_result.md` and `repro/README.md` for details and caveats (internal small-N, single-machine self-run).

## Known Limitations

- **No encryption at rest (plaintext-at-rest)** — `data/memory.db` (WAL mode, `better-sqlite3`) is a plain, unencrypted SQLite file. `100% local & private` means no cloud or network exfiltration — it does **not** mean encrypted at rest. Anyone with filesystem access (shared machine, backup, malware, stolen device) can read preferences/lessons/interactions in plaintext. For sensitive data, use OS-level full-disk encryption (BitLocker / FileVault / LUKS) or an opt-in SQLCipher build (requires native rebuild and key management). No SQLCipher/in-code encryption is applied by default and `src/db/index.ts` documents this explicitly.

## License

[MIT](https://github.com/worakorn-prince/th-memory-mcp/blob/HEAD/LICENSE) © 2026 worakorn-prince

This project is licensed under the MIT License — see the [LICENSE](https://github.com/worakorn-prince/th-memory-mcp/blob/HEAD/LICENSE) file for the full text.