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Contextforge Mcp

  • 2 repo stars
  • Updated July 23, 2026
  • alfredoizdev/contextforge-mcp

ContextForge MCP is a MCP server that adds hosted persistent memory for Claude Code, Cursor, and GitHub Copilot sessions.

About

ContextForge MCP connects your IDE agents to hosted persistent memory so decisions, conventions, and facts survive session boundaries. developers juggling Claude Code, Cursor, and Copilot on one codebase use it to reduce re-explaining architecture every morning. The server is a thin stdio bridge: CONTEXTFORGE_API_KEY is mandatory from the ContextForge dashboard, and CONTEXTFORGE_API_URL defaults to the production API. It is not a local vector database you self-host; it is a SaaS memory layer accessed through MCP tools. Placement stays in build agent-tooling because the primary win is faster implementation loops, though memory also helps during ship reviews if you store test and security notes. Register it like any npm stdio MCP package after obtaining API credentials.

  • Persistent memory MCP for Claude Code, Cursor, and GitHub Copilot (contextforge-mcp v0.2.0)
  • Requires CONTEXTFORGE_API_KEY from contextforge.dev dashboard
  • Optional CONTEXTFORGE_API_URL override (default https://api.contextforge.dev)
  • stdio npm transport (identifier contextforge-mcp)

Contextforge Mcp by the numbers

  • Data as of Jul 24, 2026 (Skillselion catalog sync)
terminal
claude mcp add --env CONTEXTFORGE_API_KEY=YOUR_CONTEXTFORGE_API_KEY --env CONTEXTFORGE_API_URL=YOUR_CONTEXTFORGE_API_URL contextforge-mcp -- npx -y contextforge-mcp

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repo stars2
Packagecontextforge-mcp
TransportSTDIO
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Last updatedJuly 23, 2026
Repositoryalfredoizdev/contextforge-mcp

What it does

Give Claude Code, Cursor, or Copilot durable project memory through ContextForge instead of losing context every new session.

Who is it for?

Best when you're on multi-week repos and switch between Claude Code, Cursor, or Copilot and need one shared memory substrate.

Skip if: One-off scripts, teams forbidding external memory SaaS, or developers who only need ephemeral in-chat context with no cross-session recall.

What you get

After you configure contextforge-mcp with an API key, agents can read and write ContextForge memory so context carries across sessions and tools.

  • MCP tools to store and recall project memory in ContextForge
  • Shared memory usable across supported coding agents
  • Configurable API endpoint via CONTEXTFORGE_API_URL

By the numbers

  • Server package version 0.2.0 (contextforge-mcp on npm)
  • stdio transport
  • 1 required secret: CONTEXTFORGE_API_KEY; optional CONTEXTFORGE_API_URL defaulting to https://api.contextforge.dev
README.md

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

  1. Go to contextforge.dev
  2. Sign up (free tier available)
  3. Settings → API Keys → Generate API Key
  4. 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
Flag Behavior
--editor=claude Generate only CLAUDE.md
--editor=cursor Generate only .cursorrules
--editor=all Generate 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

Tool Description
memory_ingest Save knowledge to memory
memory_query Search your knowledge semantically
memory_list_items List all stored items
memory_delete Remove specific items
memory_ingest_batch Save multiple items at once
memory_delete_batch Delete items by filter

Spaces & Projects

Tool Description
memory_list_spaces List your spaces
memory_create_space Create a new space
memory_delete_space Delete a space
memory_move_space Move space to project
memory_list_projects List your projects
memory_create_project Create a new project
memory_delete_project Delete a project
memory_link_project Link directory to project
memory_unlink_project Unlink directory
memory_current_project Show linked project

GitHub Integration

Tool Description
memory_git_connect Connect a GitHub repo
memory_git_list List connected repos
memory_git_activate Activate/deactivate webhook
memory_git_sync Import existing history
memory_git_commits List synced commits
memory_git_prs List synced PRs
memory_git_disconnect Disconnect a repo

Issue Tracking

Tool Description
issues_list List your issues
issues_create Create a new issue
issues_start Mark as in progress
issues_resolve Mark as resolved
issues_resolve_by_name Resolve by title
issues_assign Assign to collaborator
issues_what_next Get recommendation

Collaboration

Tool Description
project_share Share project by email
collaborators_list List collaborators

Snapshots & Export

Tool Description
memory_snapshot_create Create a backup
memory_snapshot_list List all snapshots
memory_snapshot_restore Restore from backup
memory_snapshot_delete Delete a snapshot
memory_export Export to JSON/MD/CSV
memory_import Import from file

Utility

Tool Description
memory_stats View usage statistics
memory_relate Link two items
memory_help Show help

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

Variable Required Description
CONTEXTFORGE_API_KEY Yes Your API key from the dashboard
CONTEXTFORGE_API_URL No API endpoint (defaults to production)
CONTEXTFORGE_DEFAULT_SPACE No Default 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

Recommended MCP Servers

How it compares

Hosted persistent-memory MCP, not encrypted multi-agent chat or cloud cost FinOps.

FAQ

Who is ContextForge MCP for?

Developers using Claude Code, Cursor, or GitHub Copilot who want cross-session memory without manually pasting project briefs each time.

When should I use ContextForge MCP?

Use it at the start of a build engagement and throughout implementation whenever you need agents to remember architecture, preferences, and prior decisions.

How do I add ContextForge MCP to my agent?

Sign up at contextforge.dev, copy CONTEXTFORGE_API_KEY into your MCP client env, install contextforge-mcp (v0.2.0) via stdio, optionally set CONTEXTFORGE_API_URL, then enable the server in Claude Code or Cursor.

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