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

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

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.

推理分类下的更多 MCP 服务器

n8n Workflow Builder MCP Server

salacoste

AI-powered n8n workflow automation through natural language. MCP server enabling Claude AI & Cursor IDE to create, manage, and monitor workflows via Model Context Protocol. Multi-instance support, 17 tools, comprehensive docs. Build workflows conversationally without manual JSON

229

Agentic Resource Discovery

neuronto

Neuronto Agentic Resource Discovery (ARD) Index. Federated search across every public ARD registry, plus a verified tool index read from each MCP server's own tools/list, hybrid lexical and semantic retrieval, and ARD-Bench.

Agentic Swmm Workflow

Zhonghao1995

Agentic SWMM is an automated, auditable, and memory-informed framework for reproducible stormwater modelling, integrating QGIS and EPA SWMM through the aiswmm runtime, reusable Skills, and MCP interfaces, with QA verification, provenance tracking, calibration support, and Codex,

🐢🚀 Node.js Sandbox MCP Server

alfonsograziano

A Node.js–based Model Context Protocol server that spins up disposable Docker containers to execute arbitrary JavaScript.

154

n8n Workflow Builder MCP

ifmelate

MCP server that allow LLM in agent mode builds n8n workflows for you