CrewAI MCP Server

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.

Category
Visit Server

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.

Let's create wonders together with the power and simplicity of crewAI.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured