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The Zen of Hanzo MCP: One server to rule them all. The ultimate MCP that orchestrates all others.

Project description

Hanzo AI - The Zen of Model Context Protocol

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🥷 The Complete AI Development Ecosystem via MCP

One unified interface to orchestrate your entire development workflow.

Hanzo AI is more than an MCP server—it's a comprehensive ecosystem of interconnected development tools designed for the AI era. From interactive notebooks with multi-language support to advanced debugging, from intelligent code search to multi-agent workflows, everything works together seamlessly through the Model Context Protocol.

# Install and rule your development world
uvx hanzo-mcp

# Or use our one-click Desktop Extension
# Download from releases and double-click to install

Note on Installation: If uvx is not installed, Hanzo will automatically install it for you in your home directory. No manual setup required!

🌐 The Hanzo Ecosystem

Integrated Development Environment

graph LR
    A[Hanzo MCP] --> B[Interactive Notebooks]
    A --> C[Code Intelligence]
    A --> D[Multi-Agent System]
    A --> E[Project Management]
    
    B --> B1[Multi-Language REPL]
    B --> B2[SoS Kernels]
    B --> B3[Live Debugging]
    
    C --> C1[LSP Integration]
    C --> C2[AST Analysis]
    C --> C3[Semantic Search]
    
    D --> D1[Agent Networks]
    D --> D2[Tool Orchestration]
    D --> D3[Consensus Systems]
    
    E --> E1[Git Integration]
    E --> E2[Task Management]
    E --> E3[Quality Control]

🎯 Why Hanzo AI?

The Problem with Fragmented Tools

  • Install 10 different tools that don't talk to each other
  • Context switching between interfaces kills productivity
  • No unified way to orchestrate complex workflows
  • Missing the power of tool composition

The Hanzo Solution

  • Unified Ecosystem: 70+ tools that work together seamlessly
  • Intelligent Orchestration: Tools that understand context and collaborate
  • Interactive Development: From REPL to debugging in one interface
  • Quality Built-in: Automated review, testing, and best practices
  • Extensible Platform: Add any MCP server or custom tool

🚀 Core Capabilities

📓 Interactive Development Environment

Multi-Language Notebooks with SoS

# Work with multiple languages in one notebook
notebook(
    action="create",
    path="analysis.ipynb",
    kernels=["python3", "R", "javascript", "bash"]
)

# Write and execute code interactively
notebook(
    action="write",
    cell_type="code",
    content="""
    # Python cell
    data = load_dataset()
    processed = clean_data(data)
    """,
    kernel="python3"
)

# Step through execution line by line
notebook(
    action="step",
    cell_id="cell_123",
    lines=[1, 2, 3]  # Execute specific lines
)

# Read results and outputs
result = notebook(
    action="read",
    cell_id="cell_123",
    include_outputs=True
)

# Launch debugger for interactive debugging
debugger(
    notebook="analysis.ipynb",
    cell_id="cell_123",
    breakpoint=15
)

Interactive REPL Sessions

# Start multi-language REPL
repl(
    languages=["python", "javascript", "go"],
    project_dir="/path/to/project",
    share_context=True  # Share variables between languages
)

# Execute code with full project context
repl.execute("""
import project_module
result = project_module.process()
""", language="python")

🧠 Advanced AI Tools

Multi-Agent Workflows

# Delegate complex tasks to specialized agents
agent(
    prompts=["Find all API endpoints", "Document each endpoint", "Generate OpenAPI spec"],
    parallel=True  # Run agents concurrently
)

# Get consensus from multiple LLMs
consensus(
    prompt="Review this architecture decision",
    providers=["openai", "anthropic", "google"],
    threshold=0.8  # Require 80% agreement
)

Built-in Code Critic

# Force high-quality standards with the critic tool
critic(
    analysis="Review authentication implementation for security issues"
)
# The critic will:
# - Find potential bugs and edge cases
# - Ensure proper error handling
# - Verify test coverage
# - Check security implications
# - Suggest improvements
# - Enforce best practices

📝 Project Intelligence

Automatic Rules Discovery

# Reads your project preferences automatically
rules()  # Finds .cursorrules, .claude/code.md, etc.
# Understands your:
# - Coding standards
# - Project conventions  
# - AI assistant preferences
# - Team guidelines

Unified Todo Management

# Single tool for all task management
todo("Add authentication to API")
todo --action update --id abc123 --status in_progress
todo --action list --filter pending

🔍 Intelligent Code Intelligence

Unified Search Engine

# One search to rule them all - automatically runs in parallel:
# - Text search with ripgrep
# - AST analysis for code structure
# - Vector search for semantic meaning
# - Git history search (integrated into git tool)
# - Symbol search with LSP
# - Memory search for past discussions
search("authentication flow")

Language Server Protocol (LSP) Integration

# Full LSP support with jupyter-lsp integration
lsp(
    action="initialize",
    language="python",
    project_dir="/path/to/project"
)

# Go to definition, find references, rename symbols
lsp.goto_definition("UserService.authenticate")
lsp.find_references("API_KEY")
lsp.rename_symbol("oldFunction", "newFunction")

# Get diagnostics and hover information
diagnostics = lsp.get_diagnostics("main.py")
info = lsp.hover("mysterious_function", line=42, col=15)

Git Integration (with built-in search)

# All git operations in one tool
git("status")
git("diff", "--cached")
git("log", "--oneline", "-10")

# Git search is now part of the git tool
git("search", pattern="TODO", history=True)
git("blame", file="src/auth.py", line=42)
git("show", commit="abc123:src/main.py")

🎨 Palette System - Opinions Are Just Configurations

# Don't like our defaults? Switch instantly
palette --action activate python      # Python development focused
palette --action activate javascript  # Node.js/React optimized
palette --action activate devops     # Infrastructure tools
palette --action activate academic   # Research & documentation

# Create your own workflow
palette_create(
    name="my-workflow",
    tools=["read", "write", "edit", "search", "critic", "agent"],
    env_vars={"EDITOR": "nvim", "SEARCH": "ripgrep"}
)

🔌 MCP Server Orchestration

# Add any MCP server dynamically
mcp --action add --url "github.com/someone/their-mcp" --alias "their"

# Use their tools seamlessly
their_tool(action="whatever", params=...)

# Remove when done
mcp --action remove --alias "their"

🛠️ Comprehensive Tool Ecosystem

📝 Interactive Development

  • notebook - Multi-language notebooks with SoS (read/write/step/debug)
  • repl - Interactive multi-language REPL with shared context
  • debugger - Full debugging support with breakpoints and stepping
  • lsp - Language Server Protocol with jupyter-lsp integration

🔍 Code Intelligence

  • search - Unified multi-modal search (text/AST/vector/git/memory)
  • symbols - AST-aware navigation with tree-sitter
  • find - Fast file/directory discovery
  • grep - Pattern matching with ripgrep
  • ast - Code structure analysis

📁 File Operations

  • read/write/edit/multi_edit - Intelligent file operations
  • tree - Visual directory structures
  • watch - File monitoring with notifications
  • diff - Visual comparisons

🤖 AI & Automation

  • agent - Multi-agent task delegation
  • consensus - Multi-LLM agreement and validation
  • think - Structured reasoning workspace
  • critic - Automated code review and quality
  • batch - Parallel tool execution

🖥️ System & Process

  • bash - Command execution with session management
  • npx/uvx - Package runners with auto-install
  • process - Background process management
  • git - Complete git integration with search

📊 Data & Analytics

  • vector - Semantic search and indexing
  • sql - Database operations and queries
  • graph - Graph database operations
  • stats - Performance and usage analytics

🎯 Project Management

  • todo - Unified task management
  • rules - Project preferences discovery
  • palette - Tool configuration presets
  • mcp - Dynamic MCP server orchestration

🚀 Quick Start

Installation Methods

1. Via pip/uv (Recommended)

# Installs globally
uvx hanzo-mcp

# Don't have uv? No problem - we'll install it for you!
curl -LsSf https://pypi.org/simple/hanzo-mcp | python3

2. Desktop Extension (One-Click)

  1. Download hanzo-mcp.dxt from latest release
  2. Double-click to install in Claude Desktop
  3. Restart Claude Desktop

3. Manual Configuration

// Add to Claude Desktop config
{
  "mcpServers": {
    "hanzo": {
      "command": "uvx",
      "args": ["hanzo-mcp"],
      "env": {
        "HANZO_ALLOWED_PATHS": "/Users/you/projects"
      }
    }
  }
}

🔗 Ecosystem Integration

Everything Works Together

# Example: AI-assisted debugging workflow
# 1. Find the bug
search("null pointer exception")

# 2. Open in notebook for investigation
notebook(
    action="create",
    path="debug_session.ipynb",
    import_code="src/auth.py:42-58"
)

# 3. Set breakpoints and debug
debugger(
    notebook="debug_session.ipynb",
    breakpoints=[45, 52]
)

# 4. Get AI analysis
critic("Analyze this exception and suggest fixes")

# 5. Apply the fix
edit("src/auth.py", old="user.name", new="user?.name")

# 6. Verify with tests
bash("pytest tests/test_auth.py -v")

Tool Composition Power

  • Search → Notebook → Debug - Investigate issues interactively
  • Agent → Critic → Test - Automated quality workflows
  • LSP → AST → Edit - Intelligent refactoring
  • Git → Search → Todo - Project management workflows

🏆 Why Developers Love Hanzo

Smart Defaults

  • Auto-installs missing dependencies and language servers
  • Discovers project rules and preferences automatically
  • Parallel operations by default for speed
  • Intelligent fallbacks when tools aren't available

Quality First

  • Built-in critic for automated code review
  • Test enforcement in all workflows
  • Security scanning in operations
  • Best practices enforced by default

Truly Extensible

  • Palette system for instant context switching
  • MCP orchestration to add any server dynamically
  • Plugin architecture for custom tools
  • Everything is an API for maximum flexibility

📊 Performance

  • 65-70 tools available instantly
  • Parallel execution reduces wait times by 80%
  • Smart caching for repeated operations
  • Minimal dependencies for fast startup

🤝 Contributing

We welcome contributions! The codebase is designed for extensibility:

  1. Add a Tool: Drop a file in hanzo_mcp/tools/
  2. Create a Palette: Define tool collections
  3. Share Workflows: Contribute your configurations

See CONTRIBUTING.md for guidelines.

📚 Documentation

🌟 Testimonials

"The critic tool alone is worth it. My code quality improved overnight." - Sr. Engineer at Fortune 500

"Finally, search that actually works. It knows what I mean, not just what I type." - AI Researcher

"I threw away 15 different tools and just use Hanzo now. The palette system means I can switch from Python to DevOps to writing in seconds." - Tech Lead

📈 Project Status

  • Version: 0.7.x (Production Ready)
  • Tools: 70+ interconnected tools
  • Ecosystems: Interactive notebooks, debugging, LSP, multi-agent
  • Languages: Python, JavaScript, Go, R, Julia, Bash, and more via SoS
  • Community: Active and growing
  • Updates: Continuous improvements

🛡️ Security

  • Sandboxed execution for all operations
  • Permission system for file access
  • Audit trails for compliance
  • No telemetry without consent

🎯 The Zen of Hanzo

  1. One Tool, One Purpose - Each tool masters one thing
  2. Quality Over Quantity - Better to do it right
  3. Parallel When Possible - Time is precious
  4. Smart Defaults - It should just work
  5. Extensible Always - Your workflow, your way

Built with ❤️ by developers, for developers. Because life's too short for bad tools.

Get Started Now →

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