mindmap-mcp-server

mindmap-mcp-server

A local-first MCP server for shared memory across AI tools, enabling context capture and resume across sessions.

Category
Visit Server

README

🧠 Mind Map — MCP memory & context-handoff server

Ever lose the thread of a discussion across Claude Code, Claude Desktop, and your other AI tools? Mind Map is a small, local-first MCP server that acts as a shared memory layer across all your local MCP clients.

You capture context at the end of a session, and resume it in any other tool — no more re-explaining your project from scratch. Memory you stop using cools and decays gracefully into one-line traces (it's never silently deleted), so your shelf stays small and trustworthy instead of becoming another haystack.

Local-first by design. It runs on your machine; your memories are plain files in ~/.mindmap that never leave your control. No account, no cloud, no server to trust. Install once with npx @ravi-labs/mindmap-mcp-server install.

ChatGPT and other cloud/web clients are out of scope for now — they can't reach a local server without a public endpoint, which conflicts with local-first. See Future.

The idea in one loop

  1. Capture (effortless) — at the end of a discussion, save a portable summary.
  2. Resume (promote-on-reuse) — pull it forward in a new session. The act of reusing it is what promotes it to trusted memory. Throwaway sessions never get promoted, so they never clutter your shelf.
  3. Consolidate (automatic) — a background pass cools unused memory through tiers (šŸ”„ hot → šŸŒ¤ļø warm → ā„ļø cold) and collapses cold items to a searchable one-line trace. The moat isn't storing things — it's forgetting well.
  4. Tidy (opt-in, gamified) — a cleanliness score rewards pruning, not hoarding.

Install (one command)

Once published to npm, the whole install is:

npx @ravi-labs/mindmap-mcp-server install

This auto-detects your local MCP clients (Claude Desktop, Cursor, Windsurf) and writes the config for you, and configures Claude Code via its CLI if present. Restart your client and Mind Map's tools are there. Preview first with npx @ravi-labs/mindmap-mcp-server install --dry-run; undo with npx @ravi-labs/mindmap-mcp-server uninstall.

Data lives in ~/.mindmap/ by default — override with the MINDMAP_DIR env var.

Manual setup (if you prefer)

Every client uses the same command — npx -y @ravi-labs/mindmap-mcp-server over stdio.

Claude Code:

claude mcp add mindmap -- npx -y @ravi-labs/mindmap-mcp-server

Claude Desktop — edit claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "mindmap": {
      "command": "npx",
      "args": ["-y", "@ravi-labs/mindmap-mcp-server"]
    }
  }
}

Cursor / Windsurf / other clients — same command + args shape in that client's MCP config. Add an env block to relocate data:

{ "command": "npx", "args": ["-y", "@ravi-labs/mindmap-mcp-server"],
  "env": { "MINDMAP_DIR": "/path/to/my/memory" } }

From source (development)

git clone https://github.com/ravi-labs/mindmap-mcp-server.git && cd mindmap-mcp-server
npm install && npm run build
node dist/index.js install --local   # points clients at this checkout

Tools

Tool What it does
mindmap_capture Silently save a context summary (the effortless half of the loop).
mindmap_resume Find + return the best context for a topic; promotes on reuse.
mindmap_search Read-only search across every tier and tool.
mindmap_list Browse memories with filters.
mindmap_get Fetch one memory's full content.
mindmap_promote Explicitly bless a memory as trusted (→ hot).
mindmap_update Trim / edit / retag — the human curation moment.
mindmap_link Connect related threads (the lightweight "map").
mindmap_prune Run the consolidation pass on demand (dry_run to preview).
mindmap_forget Soft-archive to a trace, or hard delete.
mindmap_health Gamified cleanliness score (opt-in).
mindmap_tidy Batch of stalest memories to keep / trim / forget.
mindmap_config View / change decay windows and toggles.

How it stores things

~/.mindmap/
ā”œā”€ā”€ threads/<id>.json   # one file per memory (human-readable JSON)
ā”œā”€ā”€ index.json          # fast list/search index
└── config.json         # tunable thresholds + gamification toggle

Plain files you own and can inspect, grep, back up, or sync yourself. Tiers map to the mental model: hot = mem, warm = files, cold = drive (trace).

Tuning decay

// defaults (mindmap_config to change at runtime)
{
  "hotWindowMs":  7 days,    // active memory stays hot this long
  "warmWindowMs": 30 days,   // then warm; past it → cold trace
  "promotedLongevityFactor": 2,  // blessed memories decay 2Ɨ slower
  "gamification": true
}

Develop

npm run dev      # watch mode (tsx)
npm run build    # type-check + emit dist/
npm test         # end-to-end smoke tests (stdio + http) in throwaway data dirs

Future

ChatGPT / cloud clients (parked). A cloud client can't reach a local server without exposing it publicly (a tunnel or a host), which breaks the local-first promise. An HTTP transport already ships in the codebase (TRANSPORT=http, with bearer-token auth + origin allow-listing) for anyone who chooses to self-host — but it's intentionally not the default path. Revisiting ChatGPT later likely means an opt-in hosted tier with per-user encryption, a deliberate trust decision rather than a default.

Other directions:

  • Auto-capture hooks per client so the "capture" step is invisible.
  • Embedding-based semantic recall (current search is token-overlap).
  • Richer graph view of linked threads.
  • OAuth + per-user data isolation (only needed if a hosted tier ever happens).

License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured