MCP Crew AI Server

@adam-paterson

代码仓库

基本信息

分类

推理

传输方式

stdio

作者

adam-paterson

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

MCP Crew AI Server 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"
      ]
    }
  }
}

MCP Crew AI Server 工具

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点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。

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.

常见问题

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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