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contextforge-mcp

Persistent memory MCP server for Claude Code, Cursor, and GitHub Copilot. Give your AI assistants long-term memory via the Model Context Protocol.

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ContextForge MCP — Persistent Memory for Claude, Cursor & Copilot

npm version License: MIT Node.js Glama MCP

Give Claude Code, Cursor, and GitHub Copilot persistent memory across sessions via the Model Context Protocol (MCP). Stop re-explaining your project every time.

ContextForge MCP is an open-source MCP server that connects your AI coding assistants to long-term, searchable memory. Decisions, architecture notes, debugging context, and project knowledge stay available across every session — across every tool that supports MCP.

  • 🧠 Persistent memory — your AI remembers everything across sessions, days, and weeks
  • 🔍 Semantic search — find knowledge by meaning, not keywords
  • 🔗 One memory, every tool — Claude Code, Cursor, Copilot, Claude Desktop, Windsurf
  • 🐙 Git integration — sync commits and PRs automatically
  • Task tracking — issues, assignments, and project status
  • 👥 Team collaboration — share projects and memory with your team
  • 🆓 Free tier — get started without a credit card

Quick Start

1. Install

npm install -g contextforge-mcp

2. Get your API key

  • Go to contextforge.dev
  • Sign up (free tier available)
  • Settings → API Keys → Generate API Key
  • Copy your key (starts with cf_)

3. Connect to your AI tool

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "contextforge": {
      "command": "contextforge-mcp",
      "env": {
        "CONTEXTFORGE_API_KEY": "your-api-key-here"
      }
    }
  }
}

Restart Claude Desktop.

Claude Code (CLI)

claude mcp add contextforge \
  -e CONTEXTFORGE_API_KEY=your-api-key-here \
  -- contextforge-mcp

Restart Claude Code and run /mcp to verify it's connected.

Cursor

Add to your Cursor MCP settings:

{
  "mcpServers": {
    "contextforge": {
      "command": "npx",
      "args": ["contextforge-mcp"],
      "env": {
        "CONTEXTFORGE_API_KEY": "your-api-key-here"
      }
    }
  }
}

GitHub Copilot (VS Code)

Add to your Copilot MCP config:

{
  "servers": {
    "contextforge": {
      "command": "npx",
      "args": ["contextforge-mcp"],
      "env": {
        "CONTEXTFORGE_API_KEY": "your-api-key-here"
      }
    }
  }
}

4. Initialize your project (required)

Set up your project so your AI editor knows to use ContextForge memory:

npx contextforge-mcp init

By default, init auto-detects which editor your project uses and writes:

  • CLAUDE.md for Claude Code (signals: existing CLAUDE.md or .claude/ directory)
  • .cursorrules for Cursor (signals: existing .cursorrules or .cursor/ directory)

If no editor is detected, both files are generated.

Without this step, your AI will silently ignore ContextForge for memory queries — even though the MCP is connected — because the built-in auto-memory wins by default.

Override with --editor

FlagBehavior
--editor=claudeGenerate only CLAUDE.md
--editor=cursorGenerate only .cursorrules
--editor=allGenerate both, skip detection

Re-running init is idempotent — files that already contain our marker are left untouched.

Available Tools

ContextForge provides tools for Knowledge Management, GitHub Integration, Issue Tracking, and Collaboration.

Knowledge Management

ToolDescription
memory_ingestSave knowledge to memory
memory_querySearch your knowledge semantically
memory_list_itemsList all stored items
memory_deleteRemove specific items
memory_ingest_batchSave multiple items at once
memory_delete_batchDelete items by filter

Spaces & Projects

ToolDescription
memory_list_spacesList your spaces
memory_create_spaceCreate a new space
memory_delete_spaceDelete a space
memory_move_spaceMove space to project
memory_list_projectsList your projects
memory_create_projectCreate a new project
memory_delete_projectDelete a project
memory_link_projectLink directory to project
memory_unlink_projectUnlink directory
memory_current_projectShow linked project

GitHub Integration

ToolDescription
memory_git_connectConnect a GitHub repo
memory_git_listList connected repos
memory_git_activateActivate/deactivate webhook
memory_git_syncImport existing history
memory_git_commitsList synced commits
memory_git_prsList synced PRs
memory_git_disconnectDisconnect a repo

Issue Tracking

ToolDescription
issues_listList your issues
issues_createCreate a new issue
issues_startMark as in progress
issues_resolveMark as resolved
issues_resolve_by_nameResolve by title
issues_assignAssign to collaborator
issues_what_nextGet recommendation

Collaboration

ToolDescription
project_shareShare project by email
collaborators_listList collaborators

Snapshots & Export

ToolDescription
memory_snapshot_createCreate a backup
memory_snapshot_listList all snapshots
memory_snapshot_restoreRestore from backup
memory_snapshot_deleteDelete a snapshot
memory_exportExport to JSON/MD/CSV
memory_importImport from file

Utility

ToolDescription
memory_statsView usage statistics
memory_relateLink two items
memory_helpShow help

Session Presence (multi-session coordination)

Running several Claude Code sessions in parallel (worktrees, agent teams)? Each MCP process automatically registers itself as a live session and heartbeats while it runs — dead sessions expire ~10 minutes after their last heartbeat. Three tools let the agent coordinate:

ToolWhat it does
session_updateDeclare what this session is working on ("working on the auth module")
session_listSee other live sessions and their focus before touching shared areas
session_endExplicitly end this session's presence (also automatic on exit)

Recommended pattern for your CLAUDE.md: call session_list when a conversation starts; call session_update when starting or switching tasks.

Natural Language Examples

You don't need to memorize commands — just talk naturally to your AI:

# Knowledge
"Save this: we use PostgreSQL for the main database"
"What database do we use?"
"List my spaces"

# GitHub
"Connect my repo github.com/myuser/myproject"
"What commits did I make today?"
"Show PRs merged this week"

# Issues
"Create an issue: Update the login page design"
"What's pending?"
"What should I work on next?"
"Mark the login issue as done"

Environment Variables

VariableRequiredDescription
CONTEXTFORGE_API_KEYYesYour API key from the dashboard
CONTEXTFORGE_API_URLNoAPI endpoint (defaults to production)
CONTEXTFORGE_DEFAULT_SPACENoDefault space for operations

How it works

ContextForge MCP is a thin client that translates Model Context Protocol tool calls into authenticated HTTP requests against the ContextForge API. Your knowledge is stored, indexed (semantic embeddings), and retrieved on the server side — the MCP client itself is stateless.

This means:

  • No infra to manage — no local databases, no embeddings to run, no vector stores to maintain
  • Works everywhere your AI works — same memory across Claude Code, Cursor, Copilot, etc.
  • Team collaboration — shared projects sync in real time

Dashboard

Manage your memory visually at contextforge.dev:

  • View and organize your knowledge
  • Search and filter memories
  • Manage API keys and billing
  • Track issues and collaborate
  • Export and backup data

Development

# Clone and install
git clone https://github.com/alfredoizdev/contextforge-mcp.git
cd contextforge-mcp
npm install

# Build
npm run build

# Run tests
npm test

# Watch mode
npm run dev

Contributing

Issues and pull requests are welcome at github.com/alfredoizdev/contextforge-mcp.

Support

License

MIT © Alfredo Izquierdo

Keywords

mcp

FAQs

Package last updated on 07 Jul 2026

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