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Plan-MCP

by bee4come
GitHub
Python
MIT License
1
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Plan-MCP

A Model Context Protocol (MCP) server that leverages Google Gemini AI for intelligent project planning and code review.

🌟 Overview

Plan-MCP acts as an AI-powered project architect that bridges Gemini's planning capabilities with Claude's coding abilities:

  • Gemini as Architect: Analyzes requirements, creates project plans, reviews code quality

  • Claude as Developer: Implements code based on Gemini's guidance

  • Continuous Feedback Loop: Gemini reviews execution results and provides iterative improvements

🚀 Features

Plan-MCP provides complete MCP feature support, making it one of the most comprehensive MCP servers available:

✅ Complete MCP Feature Matrix

Feature

Status

Description

Resources

✅

File system access (file://, dir://, workspace://)

Prompts

✅

4 structured prompt templates for common tasks

Tools

✅

10 comprehensive tools for project management

Discovery

✅

Dynamic tool discovery (handled by FastMCP)

Sampling

✅

LLM text generation for documentation and tests

Roots

✅

Workspace navigation and project root suggestions

Elicitation

✅

Interactive user input collection

🔧 Core Tools

1. Project Planning (plan_project)

  • Break down complex requirements into structured phases and tasks

  • Generate detailed project plans with priorities and dependencies

  • Estimate effort and identify potential risks

  • Support for technical constraints and preferred tech stacks

2. Code Review (review_code)

  • Comprehensive code quality analysis

  • Security vulnerability detection

  • Performance optimization suggestions

  • Best practices and design pattern recommendations

  • Language-agnostic support

3. Execution Analysis (analyze_execution)

  • Debug runtime errors with root cause analysis

  • Provide specific code fixes with explanations

  • Evaluate if execution meets expected behavior

  • Guide iterative development with next steps

4. Directory Review (review_directory)

  • Complete project/directory analysis

  • Multi-file code quality assessment

  • Project structure recommendations

  • Security scanning across entire codebase

🎯 Advanced Features

Interactive Tools (Elicitation)

  • Interactive Project Planning: Collects user preferences and requirements dynamically

  • Interactive Code Review: Customizes review focus based on user needs

LLM Sampling

  • Documentation Generation: Auto-generates comprehensive docs for code

  • Test Generation: Creates unit tests with proper assertions and edge cases

File System Resources

  • File Access: Read individual files with file:// URIs

  • Directory Access: Access entire directories with dir:// URIs

  • Workspace Navigation: Current workspace info with workspace://current

Workspace Management (Roots)

  • Workspace Roots: Lists available workspace directories

  • Project Suggestions: Recommends appropriate project locations by type

Prompt Templates

  • Code Review Template: Structured code review prompts

  • Project Planning Template: Interactive planning conversations

  • Debug Assistant: Systematic debugging guidance

  • Architecture Review: System architecture analysis

📋 Prerequisites

  • Python 3.10 or higher

  • Google Gemini API key

  • Claude Code (for MCP integration)

🛠️ Installation

Quick Start with uvx (Recommended)

# Install and run directly with uvx uvx plan-mcp # Or add to Claude Code claude mcp add plan-mcp -- uvx plan-mcp

Traditional pip Installation

# Install from PyPI pip install plan-mcp # Run the server plan-mcp

🔧 Configuration

Set up your Gemini API key

export GEMINI_API_KEY="your_gemini_api_key_here"

Or create a .env file:

GEMINI_API_KEY=your_gemini_api_key_here GEMINI_MODEL=gemini-1.5-pro LOG_LEVEL=INFO

Claude Code Integration

🚀 Method 1: Direct from GitHub (Recommended)

Run directly from GitHub using uv without local installation:

# Team/project configuration (recommended) claude mcp add -s project plan-mcp -- uv tool run --from git+https://github.com/bee4come/plan-mcp.git plan-mcp

This creates a .mcp.json file in your project root. For secure API key management, edit the file:

🔧 Method 2: Local Installation (Recommended)

Install locally for reliable connection:

# Clone and install dependencies git clone https://github.com/bee4come/plan-mcp.git cd plan-mcp pip install mcp google-generativeai python-dotenv pydantic loguru rich # Add to Claude Code claude mcp add -s project plan-mcp -- python run_mcp.py

✅ Verify Installation

Check if the MCP server is working:

# List MCP servers claude mcp list # Check server details claude mcp get plan-mcp # Test in Claude Code by typing: /mcp
{ "mcpServers": { "plan-mcp": { "command": "uv", "args": [ "tool", "run", "--from", "git+https://github.com/bee4come/plan-mcp.git", "plan-mcp" ], "env": { "GEMINI_API_KEY": "${GEMINI_API_KEY}" } } } }

Alternative Configuration Options

Personal global configuration:

claude mcp add -s user plan-mcp -e GEMINI_API_KEY=your_api_key -- uv tool run --from git+https://github.com/bee4come/plan-mcp.git plan-mcp

Local testing configuration:

claude mcp add plan-mcp -e GEMINI_API_KEY=your_api_key -- uv tool run --from git+https://github.com/bee4come/plan-mcp.git plan-mcp

Managing MCP Services

# List all services claude mcp list # Get service details claude mcp get plan-mcp # Check status in Claude Code # Type /mcp command to view connection status

💻 Usage

Once configured, you can use these tools in Claude Code:

1. Create a project plan

Use the plan_project tool to create a plan for building a REST API for task management with user authentication

2. Review code

Use the review_code tool to review this Python function for security and performance issues: [paste code]

3. Review entire directory/project

Use the review_directory tool to review my entire Python project at /path/to/project for security and code quality issues

4. Analyze execution errors

Use the analyze_execution tool to help me debug this error: [paste code and error]

5. Access files and directories

You can now ask Claude to analyze files directly: "Please review the code in file:///path/to/my/project and suggest improvements"

🏗️ Architecture

plan-mcp/ ├── plan_mcp/ │ ├── api/ # Gemini API integration │ ├── tools/ # MCP tools (planner, reviewer, analyzer) │ ├── prompts/ # System prompts for Gemini │ ├── utils/ # Utilities (logging, etc.) │ ├── config.py # Configuration management │ ├── models.py # Pydantic data models │ └── server.py # MCP server implementation └── README.md

🤝 Workflow Example

  1. Human → Claude: "Help me build a web scraper"

  2. Claude → Plan-MCP: Requests project plan

  3. Plan-MCP → Gemini: Analyzes requirements

  4. Gemini → Plan-MCP: Returns structured plan

  5. Plan-MCP → Claude: Delivers plan

  6. Claude: Implements first task

  7. Claude → Plan-MCP: Submits code for review

  8. Plan-MCP → Gemini: Reviews code

  9. Gemini → Plan-MCP: Provides feedback

  10. Plan-MCP → Claude: Delivers improvements

  11. Cycle continues...

📚 API Reference

Tools

plan_project

  • Description: Create a comprehensive project plan

  • Parameters:

    • description (required): Project description

    • requirements: List of specific requirements

    • constraints: Project constraints

    • tech_stack: Preferred technologies

review_code

  • Description: Review code for quality and issues

  • Parameters:

    • code (required): Code to review

    • language (required): Programming language

    • context: Additional context

    • focus_areas: Specific areas to focus on

analyze_execution

  • Description: Analyze execution results and debug errors

  • Parameters:

    • code (required): Code that was executed

    • execution_output (required): Output or error messages

    • expected_behavior: What the code should do

    • error_messages: Specific error messages

    • language: Programming language (default: python)

🧪 Development

Set up development environment

# Clone the repository git clone https://github.com/bee4come/plan-mcp.git cd plan-mcp # Install in development mode pip install -e ".[dev]" # Run tests pytest

Code quality

# Format code black plan_mcp/ # Lint code ruff check plan_mcp/ # Type checking mypy plan_mcp/

🐛 Troubleshooting

Common Issues

  1. "GEMINI_API_KEY not found"

    • Ensure your API key is set in environment variables: export GEMINI_API_KEY="your_key_here"

    • Or create a .env file in your working directory with GEMINI_API_KEY=your_key_here

    • Get your API key from: https://makersuite.google.com/app/apikey

  2. Connection errors

    • Verify your internet connection

    • Check if the Gemini API is accessible

    • Ensure your API key has proper permissions

  3. MCP connection issues

    • Restart Claude Code after configuration

    • Check that the server starts without errors

    • Look at Claude Code logs for errors

📄 License

MIT License - see LICENSE file for details

🙏 Acknowledgments

  • Google Gemini for powerful AI capabilities

  • Anthropic for Claude and the MCP protocol

  • The open-source community for inspiration

This server cannot be installed

-
security - not tested
A
license - permissive license
-
quality - not tested

How are these scores calculated?

An MCP server that uses Google Gemini AI to analyze requirements, create project plans, review code quality, and provide execution analysis feedback for software development projects.

  1. 🌟 Overview
    1. 🚀 Features
      1. ✅ Complete MCP Feature Matrix
      2. 🔧 Core Tools
      3. 🎯 Advanced Features
    2. 📋 Prerequisites
      1. 🛠️ Installation
        1. Quick Start with uvx (Recommended)
        2. Traditional pip Installation
      2. 🔧 Configuration
        1. Set up your Gemini API key
        2. Claude Code Integration
      3. 💻 Usage
        1. 1. Create a project plan
        2. 2. Review code
        3. 3. Review entire directory/project
        4. 4. Analyze execution errors
        5. 5. Access files and directories
      4. 🏗️ Architecture
        1. 🤝 Workflow Example
          1. 📚 API Reference
            1. Tools
          2. 🧪 Development
            1. Set up development environment
            2. Code quality
          3. 🐛 Troubleshooting
            1. Common Issues
          4. 📄 License
            1. 🙏 Acknowledgments

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