yellhorn-mcp 0.2.0

Yellhorn MCP server uses Gemini 2.5 pro to generate detailed work plans and review pull requests.

Yellhorn MCP

A Model Context Protocol (MCP) server that exposes Gemini 2.5 Pro capabilities to Claude Code for software development tasks.

Features

• Generate Work Plans: Creates GitHub issues with detailed implementation plans based on your codebase, with customizable title and detailed description
• Isolated Development Environments: Automatically creates Git worktrees and linked branches for streamlined, isolated development workflow
• Review Code Diffs: Evaluates pull requests against the original work plan with full codebase context and provides detailed feedback
• Seamless GitHub Integration: Automatically creates labeled issues, posts reviews as PR comments with references to original issues, and handles asynchronous processing
• Context Control: Use .yellhornignore files to exclude specific files and directories from the AI context, similar to .gitignore

Installation

# Install from PyPI
pip install yellhorn-mcp

# Install from source
git clone https://github.com/msnidal/yellhorn-mcp.git
cd yellhorn-mcp
pip install -e .

Configuration

The server requires the following environment variables:

• GEMINI_API_KEY: Your Gemini API key (required)
• REPO_PATH: Path to your repository (defaults to current directory)
• YELLHORN_MCP_MODEL: Gemini model to use (defaults to "gemini-2.5-pro-exp-03-25")

The server also requires the GitHub CLI (gh) to be installed and authenticated.

Usage

Running the server

# As a standalone server
yellhorn-mcp --repo-path /path/to/repo --host 127.0.0.1 --port 8000

# Using the MCP CLI
mcp dev yellhorn_mcp.server

# Install as a permanent MCP server for Claude Desktop
mcp install yellhorn_mcp.server

# Set environment variables during installation
mcp install yellhorn_mcp.server -v GEMINI_API_KEY=your_key_here -v REPO_PATH=/path/to/repo

Integration with Claude Code

When working with Claude Code, you can use the Yellhorn MCP tools by:

1. Starting a project task:

   Please generate a work plan with title "[Your Title]" and detailed description "[Your detailed requirements]"
   

2. Navigate to the created worktree directory:

   cd [worktree_path]  # The path is returned in the response
   

3. View the work plan if needed:

   # While in the worktree directory
   Please get the current work plan for this worktree
   

4. Make your changes and submit them:

   # While in the worktree directory
   Please commit my changes and create a PR with title "[PR Title]" and body "[PR Description]"
   

Tools

generate_work_plan

Creates a GitHub issue with a detailed work plan based on the title and detailed description. Also creates a Git worktree with a linked branch for isolated development.

Input:

• title: Title for the GitHub issue (will be used as issue title and header)
• detailed_description: Detailed description for the workplan

Output:

• JSON string containing:
  • issue_url: URL to the created GitHub issue
  • worktree_path: Path to the created Git worktree directory

get_workplan

Retrieves the work plan content (GitHub issue body) associated with the current Git worktree.

Note: Must be run from within a worktree created by 'generate_work_plan'.

Input:

• No parameters required

Output:

• The content of the work plan issue as a string

submit_workplan

Submits the completed work from the current Git worktree. Stages all changes, commits them, pushes the branch, creates a GitHub Pull Request, and triggers an asynchronous code review against the associated work plan issue.

Note: Must be run from within a worktree created by 'generate_work_plan'.

Input:

• pr_title: Title for the GitHub Pull Request
• pr_body: Body content for the GitHub Pull Request
• commit_message: Optional commit message (defaults to "WIP submission for issue #X")

Output:

• The URL of the created GitHub Pull Request

Development

# Install development dependencies
pip install -e ".[dev]"

# Run tests
pytest

CI/CD

The project uses GitHub Actions for continuous integration and deployment:

• Testing: Runs automatically on pull requests and pushes to the main branch

  • Linting with flake8
  • Format checking with black
  • Testing with pytest

• Publishing: Automatically publishes to PyPI when a version tag is pushed

  • Tag must match the version in pyproject.toml (e.g., v0.1.5)
  • Requires a PyPI API token stored as a GitHub repository secret (PYPI_API_TOKEN)

To release a new version:

1. Update version in pyproject.toml
2. Commit changes: git commit -am "Bump version to X.Y.Z"
3. Tag the commit: git tag vX.Y.Z
4. Push changes and tag: git push && git push --tags

For more detailed instructions, see the Usage Guide.

License

MIT