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Scanpy-MCP

Natural language interface for scRNA-Seq analysis with Scanpy through MCP.

đŸĒŠ What can it do?

  • IO module like read and write scRNA-Seq data

  • Preprocessing module,like filtering, quality control, normalization, scaling, highly-variable genes, PCA, Neighbors,...

  • Tool module, like clustering, differential expression etc.

  • Plotting module, like violin, heatmap, dotplot

❓ Who is this for?

  • Anyone who wants to do scRNA-Seq analysis natural language!

  • Agent developers who want to call scanpy's functions for their applications

🌐 Where to use it?

You can use scanpy-mcp in most AI clients, plugins, or agent frameworks that support the MCP:

  • AI clients, like Cherry Studio

  • Plugins, like Cline

  • Agent frameworks, like Agno

📚 Documentation

scmcphub's complete documentation is available at https://docs.scmcphub.org

đŸŽŦ Demo

A demo showing scRNA-Seq cell cluster analysis in a AI client Cherry Studio using natural language based on scanpy-mcp

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

đŸŽī¸ Quickstart

Install

Install from PyPI

pip install scanpy-mcp

you can test it by running

scanpy-mcp run

run scnapy-mcp locally

Refer to the following configuration in your MCP client:

check path

$ which scanpy /home/test/bin/scanpy-mcp
"mcpServers": { "scanpy-mcp": { "command": "//home/test/bin/scanpy-mcp", "args": [ "run" ] } }

run scnapy-mcp remotely

Refer to the following configuration in your MCP client:

run it in your server

scanpy-mcp run --transport shttp --port 8000

Then configure your MCP client in local AI client, like this:

"mcpServers": { "scanpy-mcp": { "url": "http://localhost:8000/mcp" } }

🤝 Contributing

If you have any questions, welcome to submit an issue, or contact me(hsh-me@outlook.com). Contributions to the code are also welcome!

Citing

If you use scanpy-mcp in for your research, please consider citing following work:

Wolf, F., Angerer, P. & Theis, F. SCANPY: large-scale single-cell gene expression data analysis. Genome Biol 19, 15 (2018). https://doi.org/10.1186/s13059-017-1382-0

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security - not tested
A
license - permissive license
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quality - not tested

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