graphmemory

graphmemory

An MCP server that builds a semantic graph memory from a project directory, indexing documentation and code into graph structures and exposing 70+ MCP tools for search, knowledge management, task management, and more.

Category
Visit Server

README

graphmemory

npm CI License: ELv2 codecov

An MCP server that builds a semantic graph memory from a project directory. Indexes markdown docs, TypeScript/JavaScript source code, and all project files into graph structures, then exposes them as 70 MCP tools + REST API + Web UI.

graphmemory dashboard

Quick start

npm install -g @graphmemory/server
cd /path/to/my-project
graphmemory serve

That's it. No config file needed — the current directory becomes your project. Open http://localhost:3000 for the web UI.

The embedding model (~560 MB) downloads on first startup and is cached at ~/.graph-memory/models/.

Connect an MCP client

Claude Code:

claude mcp add --transport http --scope project graph-memory http://localhost:3000/mcp/my-project

Claude Desktop — add via Settings > Connectors, enter the URL:

http://localhost:3000/mcp/my-project

Cursor / Windsurf / other clients — enter the URL directly in settings:

http://localhost:3000/mcp/my-project

The project ID is your directory name. Multiple clients can connect simultaneously.

With a config file

For multi-project setups, custom embedding models, auth, or workspaces — create graph-memory.yaml:

projects:
  my-app:
    projectDir: "/path/to/my-app"
  docs-site:
    projectDir: "/path/to/docs"
    graphs:
      code:
        enabled: false
graphmemory serve --config graph-memory.yaml

See docs/configuration.md for full reference and graph-memory.yaml.example for all options.

Docker

docker run -d \
  --name graph-memory \
  -p 3000:3000 \
  -v $(pwd)/graph-memory.yaml:/data/config/graph-memory.yaml:ro \
  -v /path/to/my-app:/data/projects/my-app:ro \
  -v graph-memory-models:/data/models \
  ghcr.io/graph-memory/graphmemory-server

Docker Compose:

services:
  graph-memory:
    image: ghcr.io/graph-memory/graphmemory-server
    ports:
      - "3000:3000"
    volumes:
      - ./graph-memory.yaml:/data/config/graph-memory.yaml:ro
      - /path/to/my-app:/data/projects/my-app
      - models:/data/models
    restart: unless-stopped
    depends_on:
      redis:
        condition: service_healthy

  redis:
    image: redis:7-alpine
    restart: unless-stopped
    volumes:
      - redis-data:/data
    healthcheck:
      test: ["CMD", "redis-cli", "ping"]
      interval: 10s
      timeout: 3s
      retries: 3

volumes:
  models:
  redis-data:

Redis is optional. Remove the redis service and depends_on if you don't need shared session store or embedding cache.

See docs/docker.md for details.

What it does

Feature Description
Docs indexing Parses markdown into heading-based chunks with cross-file links and code block extraction
Code indexing Extracts AST symbols (functions, classes, interfaces) via tree-sitter
File index Indexes all project files with metadata, language detection, directory hierarchy
Knowledge graph Persistent notes and facts with typed relations and cross-graph links
Task management Kanban workflow with priorities, assignees, and cross-graph context
Skills Reusable recipes with steps, triggers, and usage tracking
Hybrid search BM25 keyword + vector cosine similarity with BFS graph expansion
Real-time File watching + WebSocket push to UI
Multi-project One process manages multiple projects from a single config
Workspaces Share knowledge/tasks/skills across related projects
Auth & ACL Password login (JWT), API keys, OAuth 2.0 (PKCE), 4-level access control

70 MCP tools

Group Tools
Context get_context
Docs docs_list_files, docs_get_toc, docs_search, docs_get_node, docs_search_files, docs_find_examples, docs_search_snippets, docs_list_snippets, docs_explain_symbol, docs_cross_references
Code code_list_files, code_get_file_symbols, code_search, code_get_symbol, code_search_files
Files files_list, files_search, files_get_info
Knowledge notes_create, notes_update, notes_delete, notes_get, notes_list, notes_search, notes_create_link, notes_delete_link, notes_list_links, notes_find_linked, notes_add_attachment, notes_remove_attachment
Tasks tasks_create, tasks_update, tasks_delete, tasks_get, tasks_list, tasks_search, tasks_move, tasks_reorder, tasks_link, tasks_create_link, tasks_delete_link, tasks_find_linked, tasks_add_attachment, tasks_remove_attachment
Epics epics_create, epics_update, epics_delete, epics_get, epics_list, epics_search, epics_link_task, epics_unlink_task
Skills skills_create, skills_update, skills_delete, skills_get, skills_list, skills_search, skills_recall, skills_bump_usage, skills_link, skills_create_link, skills_delete_link, skills_find_linked, skills_add_attachment, skills_remove_attachment

Web UI

Dashboard, Knowledge (notes CRUD), Tasks (kanban board with drag-drop), Skills (recipes), Docs browser, Code browser (symbols, edges, source), Files browser, Prompts (AI prompt generator), Search (cross-graph), Tools (MCP explorer), Help.

Light/dark theme. Real-time WebSocket updates. Login page when auth is configured.

Authentication

users:
  alice:
    name: "Alice"
    email: "alice@example.com"
    apiKey: "mgm-key-abc123"
    passwordHash: "$scrypt$65536$..."   # generated by: graphmemory users add

server:
  jwtSecret: "your-secret"
  defaultAccess: rw
  redis:                              # optional: session store + embedding cache
    enabled: true
    url: "redis://localhost:6379"
  • UI login: email + password → JWT cookies (httpOnly, SameSite=Strict)
  • API access: Authorization: Bearer <apiKey>
  • OAuth 2.0: Authorization Code + PKCE (S256) with frontend consent page at /ui/auth/authorize; also supports client credentials and refresh tokens
  • OAuth endpoints: /api/oauth/userinfo, /api/oauth/introspect, /api/oauth/revoke, /api/oauth/end-session
  • ACL: graph > project > workspace > server > defaultAccess (deny / r / rw)
  • Redis (optional): when server.redis is configured, used for OAuth session store and embedding cache

See docs/authentication.md.

Development

npm run dev              # tsc --watch (backend)
cd ui && npm run dev     # Vite on :5173, proxies /api → :3000
npm test                 # 1809 tests across 45 suites

Documentation

Full documentation is in docs/:

Contributing

Contributions are welcome! See CONTRIBUTING.md for guidelines.

For security vulnerabilities, see SECURITY.md.

License

Elastic License 2.0 (ELv2) — free to use, modify, and self-host. Not permitted to offer as a managed/hosted service.

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