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galprz/grep-mcp

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Grep MCP Server

A Model Context Protocol (MCP) server that provides GitHub code search capabilities through the grep.app API. This server enables AI assistants to search through millions of GitHub repositories for specific code patterns, functions, and implementations.

Features

  • GitHub Code Search: Search across millions of GitHub repositories using grep.app's powerful search index
  • Advanced Filtering: Filter results by programming language, repository, and file path
  • Smart Formatting: Results include syntax highlighting, repository grouping, and summary statistics
  • High Performance: Async implementation with proper error handling and rate limiting
  • Multiple Transport Modes: Supports both stdio and SSE (Server-Sent Events) transport
  • Rich Results: Returns file paths, line numbers, code snippets, and repository information

Requirements

  • Python: 3.10 or higher
  • Dependencies:
    • mcp - Model Context Protocol framework
    • starlette - Web framework for SSE transport
    • uvicorn - ASGI server
    • aiohttp - Async HTTP client for API requests

Installation

Using uv (Recommended)

# Install directly from PyPI
uv add grep-mcp

# Or install from source
git clone https://github.com/galperetz/grep-mcp.git
cd grep-mcp
uv sync

Using pip

pip install grep-mcp

Usage

As MCP Server (Recommended)

Add to your MCP client configuration:

{
"mcpServers": {
"grep-mcp": {
"command": "uvx",
"args": ["grep-mcp"]
}
}
}

Direct Execution

# Run with stdio transport (default)
python -m grep_mcp

# Run with SSE transport
python -m grep_mcp --transport sse --host 0.0.0.0 --port 8080

Command Line Arguments

  • --transport: Choose between stdio (default) or sse
  • --host: Host to bind to for SSE mode (default: 0.0.0.0)
  • --port: Port to listen on for SSE mode (default: 8080)

Available Tools

grep_query

Search GitHub repositories for specific code patterns.

Parameters:

  • query (required): The search query string
  • language (optional): Programming language filter (e.g., "Python", "JavaScript")
  • repo (optional): Repository filter in format "owner/repo" (e.g., "fastapi/fastapi")
  • path (optional): Path filter for specific directories (e.g., "src/")

Examples:

# Basic search
grep_query("async def main")

# Search Python files only
grep_query("FastAPI", language="Python")

# Search specific repository
grep_query("class Config", repo="fastapi/fastapi")

# Search in specific directory
grep_query("import", path="src/")

# Combined filters
grep_query("async def", language="Python", repo="fastapi/fastapi")

Response Format

The tool returns structured JSON with:

{
"query": "your search query",
"summary": {
"total_results": 12345,
"results_shown": 10,
"repositories_found": 4,
"top_languages": [
{ "language": "Python", "count": 8500 },
{ "language": "JavaScript", "count": 2000 }
],
"top_repositories": [{ "repository": "owner/repo", "count": 150 }]
},
"results_by_repository": [
{
"repository": "owner/repo",
"matches_count": 89,
"files": [
{
"file_path": "src/main.py",
"branch": "main",
"total_matches": 5,
"line_numbers": [10, 25, 30],
"language": "python",
"code_snippet": "```python\nasync def main():\n app = FastAPI()\n return app\n```"
}
]
}
]
}

Architecture

  • FastMCP Framework: Built on the FastMCP framework for easy MCP server development
  • Async HTTP Client: Uses aiohttp for non-blocking API requests
  • Response Formatting: Intelligent parsing and formatting of grep.app responses
  • Error Handling: Comprehensive error handling for API failures, timeouts, and rate limits
  • Transport Flexibility: Supports both stdio and web-based SSE transport modes

Error Handling

The server handles various error conditions gracefully:

  • Rate Limiting: Automatic detection and user-friendly error messages
  • Network Timeouts: 30-second timeout with proper error reporting
  • API Failures: Graceful handling of grep.app API issues
  • Invalid Parameters: Comprehensive parameter validation with helpful error messages

Testing

Run the test suite:

# Using uv
uv run pytest

# Using pytest directly
pytest tests/

Test coverage includes:

  • MCP server initialization
  • Tool parameter validation
  • Error handling scenarios
  • Response formatting
  • Platform compatibility

Contributing

  1. Fork the repository
  2. Create a feature branch: git checkout -b feature/amazing-feature
  3. Make your changes with tests
  4. Run the test suite: uv run pytest
  5. Format code: uv run black . && uv run isort .
  6. Commit changes: git commit -m 'Add amazing feature'
  7. Push to branch: git push origin feature/amazing-feature
  8. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

Support


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