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Mnemo Mcp

n24q02m/mnemo-mcp
7authSTDIOregistry active
Summary

A production-grade persistent memory layer that solves the context problem for long-running AI sessions. Stores facts, preferences, decisions, and skills in SQLite with FTS5 full-text search plus sqlite-vec semantic retrieval, fused via reciprocal rank fusion and reranked by a local Qwen3 cross-encoder. The capture action accepts six typed context categories and deduplicates via embeddings. Includes a temporal knowledge graph with entity resolution, LLM-driven compression of old memories, and encrypted cross-machine sync to Google Drive or S3. Ships with skill definitions that teach Claude when to commit memories and how to recall context proactively. Reach for this when you need the AI to remember conversations across sessions without manually managing context windows or paying for third-party memory APIs.

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Mnemo MCP Server

mcp-name: io.github.n24q02m/mnemo-mcp

Persistent AI memory with hybrid search and embedded sync. Open, free, unlimited.

CI codecov PyPI Docker License: MIT SafeSkill 91/100

Python SQLite MCP semantic-release Renovate

Sister projects from n24q02m (click to expand)
ProjectTaglineTag
better-code-review-graphKnowledge graph for token-efficient code reviews -- semantic search and call-...MCP
better-email-mcpIMAP/SMTP email for AI agents -- read, send, organize folders, and manage att...MCP
better-godot-mcpComposite MCP server for Godot Engine -- 17 composite tools for AI-assisted g...MCP
better-notion-mcpMarkdown-first Notion for AI agents -- pages, databases, blocks, and comments...MCP
better-telegram-mcpTelegram for AI agents -- messages, chats, media, and contacts across both bo...MCP
claude-pluginsClaude Code plugin marketplace for the n24q02m MCP servers -- install web sea...Marketplace
imagine-mcpImage and video understanding + generation for AI agents -- across Gemini, Op...MCP
jules-task-archiverChrome Extension for bulk operations on Jules tasks via batchexecute API -- a...Tooling
mcp-coreShared foundation for building MCP servers -- Streamable HTTP transport, OAut...MCP
mnemo-mcpPersistent AI memory with hybrid search and embedded sync. Open, free, unlimi...MCP
qwen3-embedLightweight Qwen3 text embedding and reranking via ONNX Runtime and GGUFLibrary
skretSecrets without the server.CLI
tacetTACET: a self-distilling neuro-symbolic cascade that amortises LLM cost in kn...Tooling
web-coreShared web infrastructure package for search, scraping, HTTP security, and st...Library
wet-mcpOpen-source MCP server for AI agents: web search, content extraction, and lib...MCP

Table of contents

  • Features
  • Status
  • Documentation
  • Tools
  • Security
  • Build from Source
  • Trust Model
  • License
Mnemo MCP server

Roadmap (current = Phase 1 / v1.x)

PhaseVersionStatusHighlights
Phase 1v1.xShippedTyped memory(action="capture") (6 context_types + dedup) -- RRF (k=60) hybrid fusion + cross-encoder rerank + temporal decay -- importance x recency archive policy + restore -- Alembic migrations -- multi-provider LLM dispatch -- plugin trinity (recall-context + memory-commit skills, SessionStart + opt-in PostToolUse hooks)
Phase 2v1.x+1ShippedLLM-driven compression of older memories + Passport sync (encrypted import/export bundle for cross-machine bootstrap) -- AES-256-GCM + Argon2id, S3 / R2 / B2 / MinIO + GDrive backends, delta-sync with LWW per row
Phase 3v2.0.0Shipped (BREAKING)Temporal knowledge graph -- bitemporal valid_from / valid_to columns -- entity resolution via embedding KNN -- entity_search / entity_graph / history actions -- KG-aware passport bundle sections -- KG_AUTO_ENABLED opt-in auto-extract on capture

Features

  • Hybrid retrieval -- FTS5 + sqlite-vec, fused via Reciprocal Rank Fusion (k=60), then re-ranked by a configurable rerank chain (RERANK_MODELS, order = litellm fallback; empty -> local qwen3-reranker) with temporal decay and importance boost
  • Typed capture -- memory(action="capture") with 6 context_types (conversation/fact/preference/skill/task/decision), embedding-based dedup, and a configurable LLM chain (LLM_MODELS, order = litellm fallback)
  • Knowledge graph -- Automatic entity extraction and relation tracking; top results boosted by graph proximity
  • Importance scoring + archive policy -- LLM-scored 0.0-1.0 importance; soft-archive when recency_factor * (1 - importance) > 1.0; restore action available
  • Auto-archive trigger -- Background sweep every Nth capture (default 100) -- no cron required
  • STM-to-LTM consolidation -- LLM summarization of related memories in a category
  • Duplicate detection -- Warns before adding semantically similar memories
  • Zero config -- Built-in local Qwen3 ONNX embedding + reranking, no API keys needed. Optional cloud providers (Jina AI, Gemini, OpenAI, Cohere)
  • Multi-machine sync -- JSONL-based merge sync via Google Drive (bundled Desktop OAuth public client)
  • Plugin trinity -- Ships /recall-context + /memory-commit skills and SessionStart + opt-in PostToolUse hooks (see docs/ARCHITECTURE.md)
  • Proactive memory -- Tool descriptions and skills guide AI to save preferences, decisions, facts at the right moment
  • LLM compression -- Per-turn compression via the multi-provider dispatcher targets ~3x token reduction at >=0.9 fact retention; graceful skip when no provider configured (see docs/compression.md)
  • Encrypted passport sync -- AES-256-GCM bundles + Argon2id KDF, S3 (R2 / B2 / MinIO) and Google Drive backends, delta-sync with last-write-wins per row (see docs/passport.md). Bootstrap via the passport-bootstrap skill.
  • Temporal knowledge graph -- Bitemporal columns (valid_from / valid_to / superseded_by) on every memory + entity-resolution dedup (embedding KNN at default 0.85 cosine threshold) + audit trail (memory_audit table with prev/new state hashes) + new actions (entity_search / entity_graph / history) + opt-in KG_AUTO_ENABLED auto-extract on capture. BREAKING for clients that called memory.get expecting historical-inclusive results: pass as_of for time-travel; default now filters to current-state (valid_to IS NULL).

Comparison vs. peers

Featuremnemo-mcpMem0LettaOpenMemory
Hybrid retrieval (FTS + vec)yes (FTS5 + sqlite-vec + RRF)yespartialyes
Cross-encoder rerank chainyes (qwen3 local + Jina + Cohere)partial (Cohere only)nono
Temporal decay scoringyes (exp half-life)nonono
Importance boost in rankyes (LLM 0.0-1.0)nonono
Soft-archive + restore policyyes (importance x recency)nonono
Self-hostable (single SQLite file)yes (zero ext deps)partial (cloud-first)yes (Postgres)yes (Postgres + Qdrant)
Multi-provider LLM dispatchyes (LLM_MODELS chain, any litellm provider)partialyespartial
Plugin trinity (skills + hooks)yes (recall-context + memory-commit)n/an/an/a
Multi-machine syncyes (GDrive bundled OAuth)yes (cloud)n/an/a
E2E-encrypted passport syncyes (AES-256-GCM + Argon2id, S3 + GDrive)nonono
LLM compression on captureyes (multi-provider, ~3x at >=0.90 retention)nonono
Backend-pluggable sync architectureyes (S3 / R2 / B2 / MinIO + GDrive)nonono
Bitemporal valid_from / valid_to queriesyes (as_of time-travel)nopartial (events only)no
Entity resolution via embedding KNNyes (cosine threshold tunable)nonono
Audit trail with state hashesyes (memory_audit table)nonono

Status

2026-05-02 -- Architecture stabilization update

Past months saw significant churn around credential handling and the daemon-bridge auto-spawn pattern. This caused multi-process races, browser tab spam, and inconsistent setup UX across plugins. The architecture is now stable: 2 clean modes (stdio + HTTP), no daemon-bridge layer, no auto-spawn from stdio.

Apologies for the instability period. If you encountered issues with prior versions, please update to the latest release and follow the current setup docs -- most prior workarounds are no longer needed.

Related plugins from the same author:

  • wet-mcp -- Web search + content extraction
  • imagine-mcp -- Image/video understanding + generation
  • better-notion-mcp -- Notion API
  • better-email-mcp -- Email management
  • better-telegram-mcp -- Telegram
  • better-godot-mcp -- Godot Engine
  • better-code-review-graph -- Code review knowledge graph

All plugins share the same architecture -- install once, learn pattern transfers.

Documentation

Full docs at mcp.n24q02m.com/servers/mnemo-mcp/setup/:

  • Setup -- install methods for Claude Code, Codex, Gemini CLI, Cursor, Windsurf, mcp.json
  • Modes overview -- stdio / local-relay / remote-relay / remote-oauth
  • Multi-user setup -- per-JWT-sub credential model

Install with AI agent -- paste this to your AI coding agent:

Install MCP server mnemo-mcp following the steps at https://raw.githubusercontent.com/n24q02m/claude-plugins/main/plugins/mnemo-mcp/setup-with-agent.md

Tools

15 MCP tools, 17 memory actions. The memory surface is exposed both as 11 specialized single-purpose tools and a legacy memory dispatcher (same actions), plus config, help, and config__open_relay:

ToolActionsDescription
add_memory, search_memory, list_memories, update_memory, delete_memory, export_memories, import_memories, memory_stats, restore_memory, archived_memories, consolidate_memories(one action each)Specialized single-purpose memory tools -- the recommended surface
memory (legacy dispatcher)add, capture, search, list, update, delete, export, import, stats, restore, archived, archive_now, consolidate, compress, entity_search, entity_graph, historyCore CRUD + typed capture (6 context_types) + hybrid search (RRF + rerank + temporal decay) + import/export + soft-archive + restore + on-demand archive sweep + LLM consolidation + LLM compression + temporal KG (entity search / graph / history)
configstatus, sync, set, warmup, setup_sync, setup_status, setup_start, setup_skip, setup_reset, setup_complete, setup_relay, sync_now, export_passport, import_passportServer status, trigger sync, update settings, pre-download embedding model, authenticate sync provider, manage HTTP setup form lifecycle, passport export/import
helptopic="memory" or topic="config"Full documentation for any tool
config__open_relay(HTTP relay mode)Open the zero-config relay setup form (registered via mcp-core)

Plugin trinity (Claude Code marketplace install):

ComponentTriggerPurpose
mnemo:recall-context skillsession start, before significant decisions, "what do I know about X?"Pulls cwd / topic-relevant memories with context_type filtering
mnemo:memory-commit skill"remember this" / "save this" / "ghi nho" / "luu lai"Typed manual capture with context_type decision tree
mnemo:knowledge-audit skillperiodic / "audit memory"Find duplicates, contradictions, stale entries; consolidate
mnemo:session-handoff skillend of sessionCapture decisions / preferences / corrections / conventions / open questions
SessionStart hookevery session initNon-blocking nudge to invoke recall-context
PostToolUse hook (opt-in)CAPTURE_AUTO_ENABLED=trueHint memory-commit after Write/Edit of CLAUDE.md / AGENTS.md / ARCHITECTURE.md / docs/*.md

MCP Resources

URIDescription
mnemo://statsDatabase statistics and server status

MCP Prompts

PromptParametersDescription
save_summarysummaryGenerate prompt to save a conversation summary as memory
recall_contexttopicGenerate prompt to recall relevant memories about a topic

Security

  • Graceful fallbacks -- Cloud → Local embedding, no cross-mode fallback
  • Sync token security -- OAuth tokens stored at ~/.mnemo-mcp/tokens/ with 600 permissions
  • Input validation -- Sync provider, folder, remote validated against allowlists
  • Error sanitization -- No credentials in error messages

Build from Source

git clone https://github.com/n24q02m/mnemo-mcp.git
cd mnemo-mcp
uv sync
uv run mnemo-mcp

Trust Model

This plugin implements TC-Local (machine-bound, single trust principal). The mode/storage/encryption breakdown below is the full classification.

ModeStorageEncryptionWho can read your data?
stdio (default)~/.mnemo-mcp/config.jsonAES-GCM, machine-bound keyOnly your OS user (file perm 0600)
HTTP self-hostSame as stdioSameOnly you (admin = user)
HTTP multi-user remote (PUBLIC_URL)Per-JWT-sub credential storeAES-GCMOnly the authenticated user (per-sub isolation)

License

MIT -- See LICENSE.

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Configuration

API_KEYSsecret

API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.

Categories
AI & LLM ToolsSearch & Web Crawling
Registryactive
Packagemnemo-mcp
TransportSTDIO
AuthRequired
UpdatedJun 9, 2026
View on GitHub

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