Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Scanpy-MCP Perform clustering on the dataset and generate a UMAP plot."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Natural language interface for scRNA-Seq analysis with Scanpy through MCP.
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
Related MCP server: Liana-MCP
Anyone who wants to do scRNA-Seq analysis natural language!
Agent developers who want to call scanpy's functions for their applications
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
scmcphub's complete documentation is available at https://docs.scmcphub.org
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
Install from PyPI
pip install scanpy-mcpyou can test it by running
scanpy-mcp runRefer 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"
]
}
}Refer to the following configuration in your MCP client:
run it in your server
scanpy-mcp run --transport shttp --port 8000Then configure your MCP client in local AI client, like this:
"mcpServers": {
"scanpy-mcp": {
"url": "http://localhost:8000/mcp"
}
}If you have any questions, welcome to submit an issue, or contact me(hsh-me@outlook.com). Contributions to the code are also welcome!
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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