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  1. Home
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  3. Mneme
Mneme logo
Health: ActiveRecent health check succeeded.Last checked 9/11/2026, 3:45:45 PM

Mneme

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View Repository2 GitHub StarsTotal stargazers on GitHub for the source repository (2 stars).Visit Website

Vault-native markdown memory for Claude Code and MCP clients with fast, accountable session recording and search.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

One-click editor setup isn’t available for this listing yet β€” we don’t have a confirmed install command, and we’d rather show nothing than point your editor at the wrong package or host. Follow the project’s own setup instructions, linked above.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ
No confirmed setup config for this listing yet. We only publish a config block when the install details come from the project itself β€” its README, its docs, or a verified owner. We haven’t found those for TheGoatPsy/mneme, and we’d rather show nothing than a guess you’d paste into your client. Follow the project’s own setup instructions for the current steps.
Install Tool Schemas (9) Directory Badge Claim listing Alternatives🧠 More in Knowledge & Memory

Overview

This server provides persistent memory for AI sessions by storing all session data as plain markdown files in a user-owned vault directory, indexed with SQLite FTS5 for efficient search. It integrates lifecycle hooks for Claude Code and supports other MCP clients via an open adapter, ensuring no LLM calls occur during session closure. Use it when you need transparent, editable, and fast memory storage that can be fully inspected and managed outside the AI environment.

Use cases

β€’Record AI session transcripts as markdown files
β€’Search session history efficiently using full-text search
β€’Integrate accountable memory into Claude Code workflows
β€’Manage session data in a user-controlled vault directory
β€’Extend memory capabilities to other MCP clients via adapter

Key features

β€’Stores session data as plain markdown files with frontmatter
β€’Indexes vault content using SQLite FTS5 for fast retrieval
β€’No network or LLM calls on session stop hooks to ensure speed
β€’Atomic file writes with cross-process locking for consistency
β€’Benchmarked with deterministic regression tests for quality
β€’Supports lifecycle hooks for Claude Code and open adapter for others

Capabilities & Tool Schemas (9) ~425 tokensApproximate context cost of this server’s tool schemas (~4 chars/token), before any tool is called. Actual usage depends on your client and model.Self-reported Self-reportedParsed from the repository README, not verified against a live server β€” may be incomplete or out of date.

Inspect callable tools, capabilities, and parameters exposed to AI agents by Mneme.

mneme_search

FTS5 BM25 retrieval over the vault with Turkish casefold normalization, plus date, memory-type, and scope filters. Returns ranked hits and EvidenceCards carrying content hashes, trust, confidence, and the backend that actually ran.

mneme_recall

Retrieves indexed documents by session identifier, date range, and scope. Returns paths, titles, modification times, memory types, and optionally the full markdown body.

mneme_write

Atomically appends or replaces a markdown section in a vault file. Enforces vault path containment and redacts private spans before storage.

mneme_summarize

Groups FTS5 matches for a topic by vault directory within optional date and scope filters. Graphiti enrichment appears only when that optional local graph integration is configured.

mneme_timeline

Returns scope-restricted references for a subject in chronological order. Graphiti facts and bi-temporal filtering appear only when the optional local graph integration is available.

mneme_prime

Builds a token-budgeted preflight context bundle from recent sessions and topic-relevant matches. A caller session identifier enables per-session injection deduplication and full, keypoints, or reference formatting.

Documentation Overview

mneme β€” vault-native memory for Claude Code

mneme Record

Vault-native memory for Claude Code. Markdown is ground truth.

mneme-core on PyPI mneme-cc-plugin on PyPI mneme-mcp-server on npm CI Apache-2.0 Python versions DOI

Every session starts from zero. You re-explain the same architecture, the same constraints, the same decision you already settled yesterday, and the tools that promise to fix it mostly store your conversation history in opaque SQLite blobs and call an LLM every time you finish a session. The record of your own work ends up somewhere you cannot read, cannot grep, and cannot take with you.

mneme records what happened in each Claude Code session as plain markdown files in a directory you own (the vault) and indexes them with SQLite FTS5. The next session opens with a preflight block β€” today's headings, a git status summary, and the five most recently modified session documents β€” and the agent queries the index on demand through mneme_search.

Here is the file the Stop hook writes. The frontmatter, heading, and summary shape come from packages/mneme-cc-plugin/src/mneme_cc_plugin/hooks/stop.py and packages/mneme-core/src/mneme_core/distill/templates/summary-en.md; the contents below are illustrative.

markdown
---
id: session-2026-07-24
type: session
created: 2026-07-24T09:12:41.087213+00:00
schema_version: 1
---
# Sessions 2026-07-24

## 09:12 session a3f19c2e
transcript: `~/.claude/projects/mneme/a3f19c2e.jsonl`

**Session intent**: make the retrieval guard fail on the negative probe too

**Files touched**

- `benchmarks/retrieval/regression_guard.py`
- `benchmarks/retrieval/baseline.json`

**Tool activity** (34 events, 08:41:02 β†’ 09:12:38)

- Edit: 11
- Bash: 9
- Read: 8

*Deterministic extractive summary (zero-LLM). Edit freely β€” this file is yours.*
bash
pipx install mneme-cc-plugin && mneme install

That installs the plugin and registers the lifecycle hooks; mneme doctor verifies the result, and profiles and per-client installs are under Three-Tier Install. Claude Code registers six hook events; Codex and Antigravity map four. Any other MCP client (Kimi, Qwen, Cline, Cursor) gets the ten MCP tools through the open adapter, with no lifecycle hooks and no automatic capture.

  • What it stores is a file you can open. When a session has actually changed something in the vault, the Stop hook appends a timestamped ## HH:MM session block to vault/sessions/YYYY-MM-DD.md with type: session frontmatter, written atomically under a cross-process lock; mneme index rebuild reconstructs the FTS5 index over every markdown file in the vault, so the database is derived state you can delete.
  • Closing a session costs nothing and takes 2 ms. "No LLM call on the critical path" is enforced in CI rather than promised in prose. tools/spec_verify.py parses all six lifecycle hook modules and fails the build on any import of seven network-capable roots (anthropic, openai, requests, httpx, urllib.request, urllib3, aiohttp), and packages/mneme-cc-plugin/tests/integration/test_c3_no_network.py re-checks the full transitive import closure of the three hot-path hooks at runtime, where a static scan cannot see. The Stop-hook proxy benchmark measures 2 ms at p95 over 100 sessions against a 1000 ms ceiling: benchmarks/latency/p95_guard.py enforces that ceiling inside the same path-scoped benchmark workflow described below, and packages/mneme-cc-plugin/tests/unit/test_stop_performance.py re-checks it over 100 real Stop calls on every CI run, which carries no path filter.
  • Search quality cannot silently degrade. A pull request that drops production-FTS5 nDCG@5 more than 0.02 below the locked baseline (0.8006, reported as 0.801), drops Recall@10 more than 0.05 below 1.00, or fails the out-of-vocabulary negative probe fails the build β€” benchmarks/retrieval/regression_guard.py, run by .github/workflows/bench.yml on every pull request and every push to main that touches packages/mneme-core, packages/mneme-mcp, benchmarks/, or the workflow file itself.

Scope and limits

Those numbers come from the in-repo benchmark suite, seeded with MNEME_BENCH_SEED=42. Benchmark A uses a 500-document corpus. Benchmark E uses its default 300-document, 30-query fixture. Reproduce with make bench-all. Both figures above β€” the 0.801 and the 2 ms β€” carry the note that governs every figure in this README:

Note: All figures below are deterministic regression anchors computed on a seeded synthetic corpus; they are not real-world quality measurements (see ADR-012).

Retrieval claims follow the reachable path. The production mneme_search path is FTS5 BM25. The Python core contains an experimental feature-hashed lexical-vector backend and an RRF fusion protocol used by unit tests and synthetic benchmarks, but that backend is not wired into the MCP server or installer. Full-profile summarize and timeline can add gated local Graphiti and Neo4j fields. A true semantic embedding backend remains roadmap.

Privacy and network. Inline <private> tag redaction at staging write with SHA256 audit log. Zero outbound network calls except opted-in compression LLM and optional local Neo4j. Compression happens in the background, opt-in, with a cost cap.

Temporal reasoning. The deterministic claim lifecycle (valid-from/to, supersedes, as-of queries, contradiction detection, temporal blame provenance time-travel) is built in on every profile β€” pure SQLite, no extra dependency. Graphiti export and LLM claim extraction remain optional and never run on the Stop or critical path.

Context Continuity Engine (opt-in). Checkpoints are plain markdown in the vault, zero-LLM, default off.

Obsidian is fully optional. A vault is simply a plain directory of markdown files. mneme requires no specific editor, no external application, and no Obsidian installation. You can work with your vault using grep, git, VS Code, or any text editor. The term "vault" is borrowed convention for a self-contained markdown directory, not a dependency on any particular tool. Because the vault is plain markdown, a user who already uses Obsidian can point it at the same directory and get rendered notes, backlinks, and graph-view navigation over the wikilinks mneme writes. The two tools coexist cleanly: mneme stores all derived state (indexes, staging, audit logs) inside a .mneme directory that Obsidian ignores as a dot folder, and mneme's indexer excludes the .obsidian settings folder from indexing, so neither tool disturbs the other. Obsidian is a convenient viewer and navigator for vault content. It is not part of mneme's capture, indexing, or retrieval path, and it must not be treated as an installation prerequisite.

The full shipped / gated / roadmap ledger is in Implementation Status; the capabilities mneme does not ship at all are listed under What 2.0 Does Not Ship Yet.

Status: 4.1.0 public release. Package, plugin, runtime, citation, and documentation version sources are kept in lockstep by tools/version_bump.py (18 sources including this line, verified in CI), so no single declared version can drift. Upgrading from an earlier line: docs/UPGRADING.md.

Tools

The MCP server registers ten tools. Every client that speaks MCP gets all ten; lifecycle hooks and automatic capture are a separate layer that only Claude Code, Codex, and Antigravity provide. The authoritative list is packages/mneme-mcp/src/tool_registry.ts.

Read the full README β†’View source on GitHub β†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks β€” not a rating.

GitHub stars
2
Stargazers on the source repository.
Last commit
Today
Most recent push to the default branch.
Tools exposed
9
Callable tools this server registers over MCP.

Reviews

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Frequently Asked Questions about Mneme

It appends timestamped markdown blocks to daily session markdown files in a user-owned vault directory.

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Technical Specs & Signals

Category🧠Knowledge & Memory
More technical detailsExpand β–Ύ
Last updatedSep 11, 2026
4/5 checks healthy over the last 32d
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Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

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