Mind MCP Server

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🧠 Mind

Your coding agent forgets. Mind remembers.

Local, persistent memory for AI coding agents. Keep decisions, discoveries, fixes, and working context available across sessions, context compaction, and tools.

Local-first · Open source · MCP

Get started · Documentation · Supported agents · Benchmarks

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Contents

• Why Mind?
• Benchmarks
• See Mind in action
• Get started
• How Mind works
• Documentation
• Contributing

Why Mind?

Most coding agents lose useful context when sessions end, context is compacted, or you switch tools. Mind gives them one local memory layer to carry knowledge forward.

• Remember what matters. Preserve decisions, constraints, bug fixes, patterns, and current references instead of rediscovering them every session.
• Continue unfinished work. Checkpoints and session summaries help agents pick up where they left off, including after compaction.
• Connect knowledge. Spaces, tags, directional links, and three memory tiers keep related information organized and useful as a project evolves.
• Share context across tools. The CLI, MCP server, HTTP API, and web app work with the same SQLite database.
• Search without an API key. Full-text retrieval works out of the box; OpenAI or OpenRouter embeddings are optional for semantic search.

Benchmarks

🏆 86.67% answer accuracy. Top-3 territory. Even without embeddings.

Mind achieved 86.67% answer accuracy on OmniMemEval LongMemEval-S, putting it in top-three territory by raw score against published results — with semantic RAG disabled.

But remembering the right answer is only one part of memory.

Mind is designed to build, connect, prioritize, and maintain knowledge over time: promote useful memories, preserve superseded decisions, link related discoveries, and recover the context needed for the next session.

Benchmark note: Mind's completed run used a stratified subset and GPT-6 Luna (low) for answering and judging, while the published comparisons use different sample sizes and configurations. The top-three comparison is indicative, not an official ranking. RAG was disabled; additional RAG-enabled tests produced similar results but are not a controlled head-to-head comparison.

Mind's benchmark methodology and results · How the memory lifecycle works

See Mind in action

Explore your memories in the web app, edit what matters, and follow relationships in the per-space Neural Map.

Get started

1. Install Mind

On macOS or Linux, run:

curl -fsSL https://raw.githubusercontent.com/GabrielMartinMoran/mind/main/scripts/install.sh | bash

The installer installs to user-local paths and installs Bun if needed. It doesn't require sudo. If your shell can't find mind, add ~/.local/bin to your PATH as instructed by the installer, then open a new terminal.

Install from source and advanced configuration

2. Connect your agents

mind setup

This configures all supported agent integrations and the shared mind-management skill. It does not install the agent applications themselves and may write configuration for agents that are not installed.

Only want one integration? Use mind setup <agent> (for example, mind setup codex). Run mind setup compatibility to see supported, partial, and unverified capabilities, or mind setup refresh to update existing Mind-managed integrations.

Supported agents and capability matrix · Agent setup details

3. Try it

mind status
mind create projects/my-project "My project"
mind add projects/my-project architecture "CLI uses command registry + atomic command modules"
mind search architecture
mind serve start

Open http://localhost:30303 to inspect your memories. Agents use Mind through its installed MCP integration; the commands above are a quick way to explore the same store yourself.

Using an agent to set up Mind? Give it the installation steps above and ask it to run mind setup, check mind status, and report mind setup compatibility results. Your agent should distinguish configured integrations from those actually validated on your machine.

How Mind works

Mind is a persistent cognitive workspace, not just a collection of notes.

1. Remember. Save reusable decisions, fixes, discoveries, and references; use checkpoints for unfinished work and summaries for completed sessions.
2. Recall. Retrieve relevant context through Mind's unified full-text search, with optional embeddings when semantic search is enabled.
3. Relate and evolve. Link memories, maintain current references, preserve superseded knowledge, and let useful memories move between active and archive tiers as their use changes.
4. Continue. Agents follow the shared mind-management skill to recover context and manage memory across sessions and handoffs, subject to their integration's capabilities.

Everything lives in one local SQLite store (mind.db). Mind also supports an experimental opt-in Markdown autosync for versioned project memories. Optional embedding providers make external API calls only when semantic search is enabled.

Memory lifecycle · Project philosophy

Documentation

Looking for something specific? Start with the documentation index:

• Agent compatibility and setup
• CLI, web UI, and MCP reference
• Search engine and query syntax
• Autosync (experimental)
• Configuration and optional semantic search
• Skill-first agent protocol

For all available CLI commands, run mind help.

Contributing

Issues and pull requests are welcome. Read CONTRIBUTING.md for contribution guidelines, tests, and quality gates, and Mind's philosophy for the project's principles.

License

MIT · Changelog

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