PraisonAI is a production-ready multi-AI agent framework with self-reflection capabilities, designed to create AI agents to automate the solution of various problems from simple tasks to complex challenges. It simplifies the construction and management of multi-agent LLM systems by integrating PraisonAI agents, AG2, and CrewAI into a low-code solution, emphasizing simplicity, customization, and effective human-machine collaboration.

The Stripe Agent Toolkit is a toolkit that supports the integration of multiple AI agent frameworks (such as OpenAI, LangChain, CrewAI, etc.) with the Stripe API. It provides support for Python and TypeScript, simplifying payment-related operations.

automcp is a tool that can easily convert existing AI agent frameworks (such as CrewAI, LangGraph, etc.) into MCP servers to achieve standardized interface access. It supports the adaptation and deployment of multiple frameworks and provides functions for quick startup and configuration.

CrewAI Enterprise - level MCP Server implementation for deploying and managing AI workflows

An AI agent and task management server based on the CrewAI framework, providing functions such as agent creation, task assignment, and workflow execution.

An MCP server based on the CrewAI framework, providing AI agent and task management functions, supporting the creation of agents, tasks, and workflows, and running automatically.

The CrewAI MCP Adapter is a Python library that extends the CrewAI adapter ecosystem by integrating the Model Context Protocol (MCP), providing comprehensive support for custom agent and tool development.

CrewAI Crew is a multi - agent AI system project based on the crewAI framework, aiming to complete complex tasks through configuration and collaboration.

A multi-agent deep research system based on MCP, integrating LinkUp search, CrewAI coordination, and the Gemini large model, providing an interactive interface through Streamlit.

The MCP Crew AI Server is a lightweight Python - based server for running and managing CrewAI workflows, supporting communication with large language models through the MCP protocol.

automcp is a tool that can convert existing AI agent frameworks (such as CrewAI and LangGraph) into MCP protocol servers, enabling standardized interface access. It supports rapid deployment, multi - framework adaptation, and provides two transmission modes: SSE and STDIO.

Demonstrate connecting the Keboola Registry API to the MCP server through the CrewAI wrapper, enabling AI agents to call registered skills.

A multi - agent deep research system based on the MCP protocol, which uses CrewAI to coordinate three professional AI agents for web search, information analysis, and content creation, supporting local AI processing and a web interface.