What is Crewai Mcp Adapter

crewai_mcp_adapter is a Python library that extends CrewAI’s adapter ecosystem by integrating support for the Model Context Protocol (MCP) and providing comprehensive tools for developing custom agents and tools.

Use cases

Use cases include building calculators, automating tasks, and creating custom agents that interact with various tools and services through the MCP protocol.

How to use

To use crewai_mcp_adapter, install it via PyPI or from source. Then, create an instance of CrewAIAdapterClient to connect to the MCP server, define an agent with tools, and execute tasks using the provided interface.

Key features

Key features include native CrewAI integration, MCP protocol support for tool integration, an easy-to-use interface for creating new adapters, type-safe implementation with Pydantic, JSON Schema validation for tool parameters, async/await support, and detailed execution metadata.

Where to use

crewai_mcp_adapter can be used in various fields such as data analysis, automation, and any domain requiring custom agent development and tool integration.

CrewAI MCP Adapter

A Python library extending CrewAI’s adapter ecosystem with Model Context Protocol (MCP) integration support and comprehensive tooling for custom agent and tool development.

Features

• 🔌 Native CrewAI integration and adapter patterns
• 🛠️ MCP protocol support for tool integration
• 🧩 Easy-to-use interface for extending and creating new adapters
• 📝 Type-safe implementation with Pydantic
• 🔍 JSON Schema validation for tool parameters
• 🚀 Async/await support
• 📊 Detailed execution metadata

Installation

You can install the package directly from PyPI:

pip install crewai-adapters

Or install from source:

pip install git+https://github.com/dshivendra/crewai_mcp_adapter.git

Quick Start

from crewai import Agent, Task
from crewai_adapters import CrewAIAdapterClient
from crewai_adapters.types import AdapterConfig

async def main():
    async with CrewAIAdapterClient() as client:
        # Connect to MCP server
        await client.connect_to_mcp_server(
            "math",
            command="python",
            args=["math_server.py"]
        )

        # Create agent with tools
        agent = Agent(
            name="Calculator",
            goal="Perform calculations",
            tools=client.get_tools()
        )

        # Execute task
        task = Task(
            description="Calculate (3 + 5) × 12",
            agent=agent
        )
        result = await task.execute()
        print(f"Result: {result}")

if __name__ == "__main__":
    import asyncio
    asyncio.run(main())

Documentation

For detailed documentation, see:

• Getting Started Guide
• API Reference
• Examples

Development

Prerequisites

• Python 3.11 or higher
• crewai package
• pydantic package
• mcp package

Install Development Dependencies

pip install -e ".[test,docs]"

Running Tests

pytest tests/ -v

Publishing

To publish a new version to PyPI:

1. Update version in pyproject.toml
2. Build the package:

   python -m build
   

3. Upload to PyPI:

   python -m twine upload dist/*
   

License

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

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.