hanzo-mcp 0.5.2

MCP implementation of Hanzo capabilities

Hanzo MCP

An implementation of Hanzo capabilities using the Model Context Protocol (MCP).

Overview

This project provides an MCP server that implements Hanzo-like functionality, allowing Claude to directly execute instructions for modifying and improving project files. By leveraging the Model Context Protocol, this implementation enables seamless integration with various MCP clients including Claude Desktop.

Features

• Code Understanding: Analyze and understand codebases through file access and pattern searching
• Code Modification: Make targeted edits to files with proper permission handling
• Enhanced Command Execution: Run commands and scripts in various languages with improved error handling and shell support
• File Operations: Manage files with proper security controls through shell commands
• Code Discovery: Find relevant files and code patterns across your project
• Project Analysis: Understand project structure, dependencies, and frameworks
• Agent Delegation: Delegate complex tasks to specialized sub-agents that can work concurrently
• Multiple LLM Provider Support: Configure any LiteLLM-compatible model for agent operations
• Jupyter Notebook Support: Read and edit Jupyter notebooks with full cell and output handling

Tools Implemented

Core File Operations

Tool	Description
read	Read one or multiple files with encoding detection and line range support
write	Create or overwrite files with content
edit	Make precise line-based edits to existing files
multi_edit	Make multiple edits to a single file in one atomic operation
directory_tree	Get a recursive tree view of directories with customizable depth and filters
content_replace	Replace patterns in file contents using regex

Search & Analysis

Tool	Description
grep	Fast pattern search across files using ripgrep
grep_ast	AST-aware code search that understands code structure
unified_search	Intelligent multi-modal search combining text, vector, AST, and symbol search
vector_search	Semantic search across indexed documents and code
vector_index	Index documents and code in project-aware vector databases

Shell & Commands

Tool	Description
run_command	Execute shell commands with timeout, environment control, and session support

Jupyter Support

Tool	Description
notebook_read	Read Jupyter notebook cells with outputs and metadata
notebook_edit	Edit, insert, or delete cells in Jupyter notebooks

Task Management

Tool	Description
todo_read	Read the current task list for tracking progress
todo_write	Create and manage structured task lists with status and priority

Advanced Tools

Tool	Description
think	Structured space for complex reasoning and analysis without making changes
dispatch_agent	Launch specialized sub-agents for concurrent task execution
batch	Execute multiple tool calls in a single operation for performance

For detailed documentation on all tools, see TOOLS_DOCUMENTATION.md.

Getting Started

🚀 Try it Instantly in Hanzo.App

No setup required! Launch this project instantly in your browser:

Quick Install

# Install using uv
uv pip install hanzo-mcp

# Or using pip
pip install hanzo-mcp

Claude Desktop Integration

To install and configure hanzo-mcp for use with Claude Desktop:

# Install the package globally
uv pip install hanzo-mcp

# Install configuration to Claude Desktop with default settings
hanzo-mcp --install

For development, if you want to install your local version to Claude Desktop:

# Clone and navigate to the repository
git clone https://github.com/hanzoai/mcp.git
cd mcp

# Install and configure for Claude Desktop
make install-desktop

# With custom paths and server name
make install-desktop ALLOWED_PATHS="/path/to/projects,/another/path" SERVER_NAME="hanzo"

# Disable write tools (useful if you prefer using your IDE for edits)
make install-desktop DISABLE_WRITE=1

After installation, restart Claude Desktop. You'll see "hanzo" (or your custom server name) available in the MCP server dropdown.

For detailed installation and configuration instructions, please refer to the documentation.

Of course, you can also read USEFUL_PROMPTS for some inspiration on how to use hanzo-mcp.

Security

This implementation follows best practices for securing access to your filesystem:

• Permission prompts for file modifications and command execution
• Restricted access to specified directories only
• Input validation and sanitization
• Proper error handling and reporting

Documentation

Comprehensive documentation is available in the docs directory. You can build and view the documentation locally:

# Build the documentation
make docs

# Start a local server to view the documentation
make docs-serve

Then open http://localhost:8000/ in your browser to view the documentation.

Development

Setup Development Environment

# Clone the repository
git clone https://github.com/hanzoai/mcp.git
cd mcp

# Install Python 3.13 using uv
make install-python

# Setup virtual environment and install dependencies
make setup

# Or install with development dependencies
make install-dev

Testing

# Run tests
make test

# Run tests with coverage
make test-cov

Building and Publishing

# Build package
make build

# Version bumping
make bump-patch    # Increment patch version (0.1.x → 0.1.x+1)
make bump-minor    # Increment minor version (0.x.0 → 0.x+1.0)
make bump-major    # Increment major version (x.0.0 → x+1.0.0)

# Manual version bumping (alternative to make commands)
python -m scripts.bump_version patch  # Increment patch version
python -m scripts.bump_version minor  # Increment minor version
python -m scripts.bump_version major  # Increment major version

# Publishing (creates git tag and pushes it to GitHub)
make publish                     # Publish using configured credentials in .pypirc
PYPI_TOKEN=your_token make publish  # Publish with token from environment variable

# Publishing (creates git tag, pushes to GitHub, and publishes to PyPI)
make patch    # Bump patch version, build, publish, create git tag, and push
make minor    # Bump minor version, build, publish, create git tag, and push
make major    # Bump major version, build, publish, create git tag, and push

# Publish to Test PyPI
make publish-test

Contributing

New contributors welcome! 🎉 We've made it easy to contribute:

Traditional approach:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Or use Hanzo Dev for AI-assisted contributions:

• Launch in Hanzo.App for instant setup
• Add new features with AI assistance
• Fix bugs automatically

See CONTRIBUTING.md for detailed guidelines.

License

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