Click on "Install 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., "@decoupler-MCPinfer pathway activities and show the 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.
decoupler-MCP
Natural language interface for scRNA-Seq analysis with decoupler through MCP.
🪩 What can it do?
IO module like read and write scRNA-Seq data
Pathway activity/Transcription factor inference
Tool module, like clustering, differential expression etc.
Plotting module, like violin, umap/tsne
❓ Who is this for?
Anyone who wants to do scRNA-Seq analysis natural language!
Agent developers who want to call decoupler's functions for their applications
🌐 Where to use it?
You can use decoupler-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
🎬 Demo
A demo showing scRNA-Seq cell cluster analysis in a AI client Cherry Studio using natural language based on decoupler-mcp
📚 Documentation
scmcphub's complete documentation is available at https://docs.scmcphub.org
🏎️ Quickstart
Install
Install from PyPI
you can test it by running
run decoupler-mcp locally
Refer to the following configuration in your MCP client:
check path
run decoupler-server remotely
Refer to the following configuration in your MCP client:
run it in your server
Then configure your MCP client in local AI client, like this:
🤝 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 decoupler-mcp in for your research, please consider citing following work:
Badia-i-Mompel P., Vélez Santiago J., Braunger J., Geiss C., Dimitrov D., Müller-Dott S., Taus P., Dugourd A., Holland C.H., Ramirez Flores R.O. and Saez-Rodriguez J. 2022. decoupleR: ensemble of computational methods to infer biological activities from omics data. Bioinformatics Advances. https://doi.org/10.1093/bioadv/vbac016