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使用自然语言进行 scRNA-Seq 分析的 MCP 服务器!

🪩 它能做什么?

  • IO 模块,例如使用自然语言读取和写入 scRNA-Seq 数据

  • 预处理模块,如过滤、质量控制、标准化、缩放、高度可变基因、PCA、邻居等。

  • 工具模块,如聚类、差异表达等。

  • 绘图模块,例如小提琴图、热图、点图

  • 细胞间通讯分析

Related MCP server: SCMCP

❓ 这是给谁的?

  • 任何想要进行 scRNA-Seq 分析自然语言的人!

  • 想要为其应用程序调用 scanpy 函数的代理开发人员

🌐 在哪里使用它?

您可以在大多数支持 MCP 的 AI 客户端、插件或代理框架中使用 scmcp:

  • AI客户端,例如Cherry Studio

  • 插件,例如 Cline

  • 代理框架,例如 Agno

🎬 演示

演示 AI 客户端 Cherry Studio 中使用基于 scmcp 的自然语言进行 scRNA-Seq 细胞聚类分析

https://github.com/user-attachments/assets/93a8fcd8-aa38-4875-a147-a5eeff22a559

🏎️ 快速入门

安装

从 PyPI 安装

pip install scmcp

你可以通过运行来测试它

scmcp run

在本地运行 scnapy-server

在您的 MCP 客户端中参考以下配置:

"mcpServers": {
  "scmcp": {
    "command": "scmcp",
    "args": [
      "run"
    ]
  }
}

远程运行 scnapy-server

在您的 MCP 客户端中参考以下配置:

在您的服务器上运行它

scmcp run --transport sse --port 8000

然后配置您的 MCP 客户端,如下所示:

http://localhost:8000/sse

🤝 贡献

如有任何疑问,欢迎提交 issue,或联系我 ( hsh-me@outlook.com )。也欢迎您为代码做出贡献!

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