ContextPacker MCP Server
Enables AI agents to fetch and pack the most relevant files from any GitHub repository for a given query, within token limits. Works with Claude Desktop, Cursor, Windsurf, and VS Code Copilot.
README
ContextPacker MCP Server
Give any MCP-compatible AI agent instant access to any GitHub repository — without pasting files manually.
"How does authentication work in expressjs/express?"
→ agent fetches exactly the relevant files, packed within your token budget
Works with Claude Desktop, Cursor, Windsurf, VS Code (GitHub Copilot), and any other MCP client.
Hosted API: contextpacker.com — 100 free requests, no card required. This is early software. If something doesn't work as expected, please open an issue — feedback is very welcome.
Tools
| Tool | Description |
|---|---|
get_context(repo_url, query, max_tokens?) |
Selects and packs the most relevant files for a question |
get_skeleton(repo_url) |
Returns the full annotated file tree (repo map) without file contents |
Both tools support public repos out of the box. For private repos, add a GitHub PAT (see below).
Quick start
Note: The package is not yet on PyPI. Use Option B (run from source) for now. PyPI /
uvxsupport is coming soon.
Option A — uvx (coming soon)
uvx contextpacker-mcp
Option B — run from source (works now)
git clone https://github.com/rozetyp/contextpacker-mcp
cd contextpacker-mcp
python -m venv .venv && source .venv/bin/activate
pip install -e .
python server.py # verify it starts
Then point your MCP client at the server.py file (see Configure your MCP client).
Get an API key
Get a free key (100 requests, no card required) at contextpacker.com.
For running without an API key, see Self-hosting.
Configure your MCP client
First clone the repo and note the full path to server.py (e.g. /Users/you/contextpacker-mcp/server.py).
Replace that path and cp_live_your_key_here with your actual values in the snippets below.
Claude Desktop
Edit ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"contextpacker": {
"command": "python3",
"args": ["/path/to/contextpacker-mcp/server.py"],
"env": {
"CONTEXTPACKER_API_KEY": "cp_live_your_key_here"
}
}
}
}
Cursor
Create or edit ~/.cursor/mcp.json (global) or .cursor/mcp.json in your project:
{
"mcpServers": {
"contextpacker": {
"command": "python3",
"args": ["/path/to/contextpacker-mcp/server.py"],
"env": {
"CONTEXTPACKER_API_KEY": "cp_live_your_key_here"
}
}
}
}
Windsurf
Edit ~/.codeium/windsurf/mcp_config.json:
{
"mcpServers": {
"contextpacker": {
"command": "python3",
"args": ["/path/to/contextpacker-mcp/server.py"],
"env": {
"CONTEXTPACKER_API_KEY": "cp_live_your_key_here"
}
}
}
}
VS Code (GitHub Copilot)
Add to .vscode/mcp.json in your project:
{
"servers": {
"contextpacker": {
"type": "stdio",
"command": "python3",
"args": ["/path/to/contextpacker-mcp/server.py"],
"env": {
"CONTEXTPACKER_API_KEY": "cp_live_your_key_here"
}
}
}
}
Private repositories
Add your GitHub Personal Access Token (needs repo scope) to the env block:
"env": {
"CONTEXTPACKER_API_KEY": "cp_live_your_key_here",
"GITHUB_PAT": "ghp_your_token_here"
}
Environment variables
| Variable | Required | Default | Description |
|---|---|---|---|
CONTEXTPACKER_API_KEY |
Yes (hosted) | — | API key from contextpacker.com |
CONTEXTPACKER_API_URL |
No | https://contextpacker.com |
Override for self-hosted instances |
GITHUB_PAT |
No | — | GitHub PAT for private repo access (repo scope) |
Self-hosting
Run the full ContextPacker server locally — no API key needed:
git clone https://github.com/rozetyp/contextpacker
cd contextpacker
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt
export LLM_API_KEY=your_gemini_or_openai_key
uvicorn context_packer.main:app --port 8000
Then in your MCP client config, omit CONTEXTPACKER_API_KEY and add:
"env": {
"CONTEXTPACKER_API_URL": "http://localhost:8000"
}
How it works
get_context(repo_url, "how does routing work?")
↓
Shallow clone (depth=1) — or warm cache hit (~1s)
↓
Build file tree, extract AST symbols per file
↓
LLM ranks and selects the most relevant files
↓
Pack selected files into Markdown within your token budget
↓
Return context with per-file reason comments
First call for a repo: 3–10s (clone + index). Subsequent calls: ~1s.
Development
git clone https://github.com/rozetyp/contextpacker-mcp
cd contextpacker-mcp
python3 -m venv .venv && source .venv/bin/activate
pip install -e .
Test with the MCP Inspector:
npx @modelcontextprotocol/inspector python3 server.py
# Opens http://localhost:6274 — test tools directly in your browser
Feedback
This is early software under active development. If you:
- Can't get it working → open an issue
- Get bad context results for a repo → let us know with a minimal example
- Want to request a new MCP client config or feature → open an issue
A ⭐ on GitHub helps more developers find this.
Contributing
Bug reports and pull requests are welcome. Please open an issue first for larger changes.
License
MIT — see LICENSE.
Recommended Servers
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.
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.
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.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
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.
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.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
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.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.