Mnemory

Plug and play.Connect mnemory and your agent immediately starts remembering user preferences, facts, decisions, and context across conversations. No system prompt changes needed.

Self-hosted and secure.Your data stays on your infrastructure. No cloud dependencies, no third-party access to your memories.

Intelligent.Uses a unified LLM pipeline for fact extraction, deduplication, and contradiction resolution in a single call. Memories are semantically searchable, automatically categorized, and expire naturally when no longer relevant.

- Zero config—uvx mnemory, connect your MCP client, done. Works out of the box with any OpenAI-compatible API.
- Intelligent extraction— A single LLM call extracts facts, classifies metadata, and deduplicates against existing memories.
- Contradiction resolution— "I drive a Skoda" + later "I bought a Tesla" = automatic update, not a duplicate.
- Two-tier memory— Fast searchable summaries in a vector store + detailed artifact storage (reports, code, research) retrieved on demand.
- AI-powered search— Multi-query semantic search with temporal awareness. Ask "What did I decide last week about the database?" and it finds the right memories.
- Memory health checks— Built-in three-phase consistency checker (fsck) detects duplicates, contradictions, quality issues, and prompt injection. Run manually or on a schedule with auto-fix.
- 10+ client support— Claude Code, ChatGPT, Open WebUI, OpenClaw, Cursor, Windsurf, Cline, OpenCode, and more. Native plugins available for automatic recall/remember.
- Built-in management UI— Dashboard, semantic search, memory browser with full CRUD, relationship graph visualization, and health check interface. No extra tools needed.
- Production ready— Qdrant for vectors, S3/MinIO for artifacts, API key or Cognis JWT authentication, per-user isolation, Kubernetes-friendly stateless HTTP.
- Secure by default— API key or Cognis JWT authentication with session-level identity binding, per-user memory isolation, anti-injection safeguards in extraction prompts.
- REST API + MCP— Dual interface with the same backend. 16 MCP tools + full REST API with OpenAPI spec. Build plugins, integrations, or use directly.
- Prometheus monitoring— Built-in/metricsendpoint with operation counters and memory gauges. Pre-built Grafana dashboard included.

mnemory needs an OpenAI-compatible API key for LLM and embeddings. It picks upOPENAI_API_KEYfrom your environment automatically.

That's it. mnemory starts onhttp://localhost:8050/mcp, stores data in~/.mnemory/.

Now connect your client — forClaude Code, add to your MCP config:

{ "mcpServers": { "mnemory": { "type": "streamable-http", "url": "http://localhost:8050/mcp", "headers": { "X-Agent-Id": "claude-code" } } } }

Start a new conversation. Memory works automatically.

Dashboard with memory breakdowns by type, category, and role

Semantic search and AI-powered find with filters

mnemory works with any MCP-compatible client. Some clients also have dedicated plugins for automatic recall/remember.

MCP= works via Model Context Protocol (LLM-driven tool calls).Plugin= dedicated integration with automatic recall/remember (no LLM tool-calling needed).

Storing:You share information naturally. mnemory extracts individual facts, classifies them (type, category, importance), checks for duplicates and contradictions against existing memories, and stores them as searchable vectors — all in a single LLM call.

Searching:Ask a question and mnemory generates multiple search queries covering different angles and associations, runs them in parallel, and reranks results by relevance. Temporal-aware — "what did I decide last week?" just works.

Recalling:At conversation start, your agent loads pinned memories (core facts, preferences, identity) plus recent context. During conversation, relevant memories are found automatically based on what you're discussing.

Maintaining:Memories have configurable TTL — context expires in 7 days, episodic memories in 90. Frequently accessed memories stay alive (reinforcement). The built-in health checker detects and fixes duplicates, contradictions, and quality issues.

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