python-mcp-agent-workshop

nnennandukwe/python-mcp-agent-workshop

3.3

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The Model Context Protocol (MCP) server is a framework for building AI agents in Python, enabling seamless integration and communication between AI tools and agents.

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Python MCP Agent Workshop

A comprehensive workshop for building AI agents using the Model Context Protocol (MCP) in Python. This project demonstrates how to create MCP servers, implement custom tools, and configure intelligent agents for code analysis.

Link to Presentation Slides

Presentation Slides

🚀 Quick Start


# Install the repository
git clone <repository-url>
cd agent-mcp-workshop-python

# Install dependencies
poetry install

# Verify setup
python3.12 verification.py

# Start the MCP server
poetry run workshop-mcp-server

# Run tests
poetry run pytest

# Use the agent (requires Qodo)
qodo keyword_analysis --set keyword="{KEYWORD_HERE}"

📋 Prerequisites

Before starting the workshop, ensure you have the following installed:

Required Software

  1. Python 3.11+

    • Download from python.org
    • Verify: python --version

  2. Poetry (Python dependency management)

    • Install: curl -sSL https://install.python-poetry.org | python3 -
    • Or via pip: pip install poetry
    • Verify: poetry --version

  3. Qodo Command (for agent execution)

Optional Tools

  • Git for version control
  • VS Code or your preferred IDE
  • Docker (for containerized deployment)

🏗️ Architecture Overview

This workshop demonstrates a complete MCP ecosystem:

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   AI Agent      │───▶│   MCP Server    │───▶│  Keyword Tool   │
│(keyword_analysis│    │   (server.py)   │    │(keyword_search) │
│     .toml)      │    │                 │    │                 │
└─────────────────┘    └─────────────────┘    └─────────────────┘
         │                       │                       │
         │                       │                       ▼
         │                       │              ┌─────────────────┐
         │                       │              │   File System   │
         │                       │              │   (Search)      │
         │                       │              └─────────────────┘
         │                       │
         ▼                       ▼
┌─────────────────┐    ┌─────────────────┐
│   Analysis      │    │   JSON-RPC      │
│   Results       │    │   Protocol      │
└─────────────────┘    └─────────────────┘

Components

  1. MCP Server (src/workshop_mcp/server.py)

    • Implements MCP protocol
    • Exposes keyword search tool
    • Handles JSON-RPC communication

  2. Keyword Search Tool (src/workshop_mcp/keyword_search.py)

    • Asynchronous file system search
    • Multi-format text file support
    • Statistical analysis and reporting

  3. AI Agent (agents/keyword_analysis.toml)

    • Intelligent keyword analysis
    • Pattern recognition
    • Refactoring recommendations

🛠️ Usage Examples

Basic Keyword Search

from workshop_mcp.keyword_search import KeywordSearchTool

tool = KeywordSearchTool()
result = await tool.execute("async", ["/path/to/codebase"])

print(f"Found {result['summary']['total_occurrences']} occurrences")
print(f"Most frequent file: {result['summary']['most_frequent_file']}")

Running the MCP Server

# Start server (listens on stdin/stdout)
poetry run workshop-mcp-server

# Or use the script entry point
poetry run python -m workshop_mcp.server

Agent Analysis

# Run keyword analysis agent
qodo keyword_analysis --set keyword="{KEYWORD_HERE}"

Testing

# Run all tests
poetry run pytest

# Run with coverage
poetry run pytest --cov=workshop_mcp

# Run specific test file
poetry run pytest tests/test_keyword_search.py -v

# Run with detailed output
poetry run pytest -v --tb=long

🔧 Development Setup

Environment Setup

  1. Clone and Install

    git clone <repository-url>
cd agent-mcp-workshop-python
poetry install

  2. Verify Installation

    python verification.py

  3. Development Dependencies

    poetry install --with dev

Code Quality Tools

# Format code
poetry run black src/ tests/

# Sort imports
poetry run isort src/ tests/

# Type checking
poetry run mypy src/

# Linting
poetry run flake8 src/ tests/

Running in Development Mode

# Install in editable mode
poetry install

# Run server with debug logging
PYTHONPATH=src poetry run python -m workshop_mcp.server

# Run tests with verbose output
poetry run pytest -v -s

📁 Project Structure

agent-mcp-workshop-python/
├── pyproject.toml              # Poetry configuration
├── README.md                   # This file
├── verification.py             # Setup verification script
├── .gitignore                  # Git ignore rules
│
├── src/workshop_mcp/           # Main package
│   ├── __init__.py             # Package initialization
│   ├── server.py               # MCP server implementation
│   └── keyword_search.py       # Keyword search tool
│
├── agents/                     # Agent configurations
│   └── keyword_analysis.toml   # Keyword analysis agent
│
└── tests/                      # Test suite
    ├── __init__.py             # Test package init
    └── test_keyword_search.py  # Comprehensive tests

🧪 Testing Strategy

The project includes comprehensive tests covering:

Unit Tests

  • Basic functionality: Keyword search across files
  • Edge cases: Empty files, binary files, permission errors
  • Concurrency: Async operations and performance
  • Error handling: Invalid inputs and system errors

Integration Tests

  • MCP protocol: Server startup and tool execution
  • File system: Real directory traversal
  • Agent configuration: TOML parsing and validation

Performance Tests

  • Large codebases: Scalability testing
  • Concurrent searches: Multi-directory operations
  • Memory usage: Resource consumption monitoring

🚨 Troubleshooting

Common Issues

  1. Python Version Error

    Error: Python 3.11+ required
Solution: Upgrade Python or use pyenv

  2. Poetry Not Found

    Error: poetry: command not found
Solution: Install Poetry from python-poetry.org

  3. MCP Import Error

    Error: No module named 'mcp'
Solution: Run 'poetry install' to install dependencies

  4. Permission Denied

    Error: Permission denied accessing files
Solution: Check file permissions and user access

  5. Agent Configuration Error

    Error: Invalid TOML configuration
Solution: Validate TOML syntax in agents/keyword_analysis.toml

Debug Mode

Enable detailed logging:

export LOG_LEVEL=DEBUG
poetry run workshop-mcp-server

Verification Script

Run the comprehensive verification:

python3.12 verification.py

This checks:

  • Python version compatibility
  • Poetry installation and configuration
  • Project structure completeness
  • Dependency installation success
  • MCP server functionality
  • Unit test execution
  • Agent configuration validity

📚 Learning Resources

MCP Protocol

Python Async Programming

Agent Development

🤝 Contributing

  1. Fork the repository
  2. Create feature branch: git checkout -b feature/amazing-feature
  3. Make changes and test: poetry run pytest
  4. Commit changes: git commit -m 'Add amazing feature'
  5. Push to branch: git push origin feature/amazing-feature
  6. Open Pull Request

Development Guidelines

  • Follow PEP 8 style guidelines
  • Add type hints to all functions
  • Write comprehensive docstrings
  • Include unit tests for new features
  • Update documentation as needed

📄 License

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

🙏 Acknowledgments

  • Model Context Protocol team for the excellent protocol specification
  • Poetry team for dependency management
  • Qodo team for agent development platform
  • Python community for async/await support

📞 Support

Happy coding! 🎉

This workshop provides a solid foundation for building production-ready MCP agents in Python. Extend and customize it for your specific use cases.