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., "@Infercnv-MCPInfer CNVs from my scRNA-seq data and show the chromosome heatmap"
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.
Infercnv-MCP
Natural language interface for Copy Number Variation (CNV) inference from scRNA-Seq data with infercnvpy through MCP.
đĒŠ What can it do?
IO module for reading and writing scRNA-Seq data, load gene position
Preprocessing module for neighbors computation and data preparation
Tool module for CNV inference, cnv score
Plotting module for chromosome heatmaps, UMAP, and t-SNE visualizations
â Who is this for?
Researchers who want to infer CNVs from scRNA-Seq data using natural language
Agent developers who want to integrate CNV analysis into their applications
đ Where to use it?
You can use infercnv-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
đ Documentation
scmcphub's complete documentation is available at https://docs.scmcphub.org
đī¸ Quickstart
Install
Install from PyPI
you can test it by running
run infercnv-mcp locally
Refer to the following configuration in your MCP client:
check path
Run infercnv-server remotely
Refer to the following configuration in your MCP client:
Run it in your server
Then configure your MCP client, like this:
đ¤ 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 infercnv-mcp in your research, please consider citing following work:
https://github.com/icbi-lab/infercnvpy