MCP Crew AI Server

Name: MCP Crew AI Server
Author: adam-paterson

@adam-paterson

代码仓库

关于 MCP Crew AI Server

MCP Crew AI Server is a lightweight Python-based server designed to run, manage and create CrewAI workflows.

#ai #mcp #agents #mcp-server

基本信息

分类

推理

运行时

python

传输方式

stdio

发布者

adam-paterson

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp-crew-ai": {
      "command": "uvx",
      "args": [
        "mcp-crew-ai",
        "--agents",
        "path/to/agents.yml",
        "--tasks",
        "path/to/tasks.yml"
      ]
    }
  }
}

工具

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概览

What is MCP Crew AI Server?

MCP Crew AI Server is a lightweight Python server that runs, manages, and creates CrewAI multi-agent workflows. It uses the Model Context Protocol (MCP) to communicate with LLMs and tools like Claude Desktop or Cursor IDE, enabling orchestration of agentic tasks without custom code.

How to use MCP Crew AI Server?

Install via pip install mcp-crew-ai (or from GitHub or clone). Run with mcp-crew-ai --agents path/to/agents.yml --tasks path/to/tasks.yml or using uvx mcp-crew-ai with the same flags. Additional options include --topic, --process, --verbose, and --variables for YAML templating.

Key features of MCP Crew AI Server

Automatically loads agent/task configs from agents.yml and tasks.yml.
Supports custom YAML paths via --agents and --tasks command arguments.
Runs workflows through the MCP run_workflow tool.
Operates locally in STDIO mode for development and testing.
Allows variable substitution in YAML files via --variables.
Offers sequential or hierarchical process types.

Use cases of MCP Crew AI Server

Automating multi-step research and reporting tasks with AI agents.
Generating content (e.g., zoo updates) by assigning roles and goals.
Running templated workflows from IDEs like Cursor or from Claude Desktop.
Rapidly prototyping CrewAI workflows without writing Python code.

FAQ from MCP Crew AI Server

What is the runtime requirement?

Python 3.11+ along with MCP SDK, CrewAI, and PyYAML.

Can I use custom configuration files?

Yes, you specify paths via --agents and --tasks command line options.

How does variable substitution work?

Use --variables with a JSON string or file path; placeholders like {topic} in YAML are replaced at runtime.

Does it support different workflow processes?

Yes, you can choose sequential (default) or hierarchical with the --process flag.

Is there a default configuration if no files are given?

No; both --agents and --tasks are required when running the server with mcp-crew-ai. The uvx mcp-crew-ai-server command uses defaults from environment variables.

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