
CrewAI MCP Server
Exposes CrewAI tools through a REST API that allows Claude and other LLMs to access web search functionality, data analysis capabilities, and custom CrewAI tools.
README
Crewai Crew
Welcome to the Crewai Crew project, powered by crewAI. This template is designed to help you set up a multi-agent AI system with ease, leveraging the powerful and flexible framework provided by crewAI. Our goal is to enable your agents to collaborate effectively on complex tasks, maximizing their collective intelligence and capabilities.
Installation
Ensure you have Python >=3.10 <3.13 installed on your system. This project uses UV for dependency management and package handling, offering a seamless setup and execution experience.
First, if you haven't already, install uv:
pip install uv
Next, navigate to your project directory and install the dependencies:
(Optional) Lock the dependencies and install them by using the CLI command:
crewai install
Customizing
Add your OPENAI_API_KEY
into the .env
file
- Modify
src/crewai/config/agents.yaml
to define your agents - Modify
src/crewai/config/tasks.yaml
to define your tasks - Modify
src/crewai/crew.py
to add your own logic, tools and specific args - Modify
src/crewai/main.py
to add custom inputs for your agents and tasks
Running the Project
Sequential Crew
To kickstart your crew of AI agents and begin task execution, run this from the root folder of your project:
$ crewai run
This command initializes the crewai Crew, assembling the agents and assigning them tasks as defined in your configuration.
This example, unmodified, will run the create a report.md
file with the output of a research on LLMs in the root folder.
Hierarchical Crew
This project also includes a hierarchical implementation where each agent is specialized in using a specific tool. To run the hierarchical crew:
$ hierarchical
or:
$ run_hierarchical
This will create a hierarchical_result.md
file with the output from the hierarchical process.
Learn more about the hierarchical implementation in the Hierarchical README.
Model Control Protocol (MCP) Integration
This project includes an MCP server that exposes CrewAI tools through a REST API. This allows Claude and other LLMs to access and utilize CrewAI tools.
Starting the MCP Server
$ start_mcp
Or you can run it directly:
$ python -m mcp.run_server
By default, the server runs on 0.0.0.0:8000
. You can customize this:
$ start_mcp --host 127.0.0.1 --port 9000
Available MCP Tools
The MCP server provides access to the following tools:
- Custom CrewAI tools
- Web search functionality
- Data analysis capabilities
For more information, see the MCP README.
Understanding Your Crew
The crewai Crew is composed of multiple AI agents, each with unique roles, goals, and tools. These agents collaborate on a series of tasks, defined in config/tasks.yaml
, leveraging their collective skills to achieve complex objectives. The config/agents.yaml
file outlines the capabilities and configurations of each agent in your crew.
Support
For support, questions, or feedback regarding the Crewai Crew or crewAI.
- Visit our documentation
- Reach out to us through our GitHub repository
- Join our Discord
- Chat with our docs
Let's create wonders together with the power and simplicity of crewAI.
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