Infercnv-MCP
Infer Copy Number Variations (CNVs) from single-cell RNA-Seq data using a natural language interface.
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
pip install infercnv-mcp
you can test it by running
infercnv-mcp run
run infercnv-mcp locally
Refer to the following configuration in your MCP client:
check path
$ which infercnv
/home/test/bin/infercnv-mcp
"mcpServers": {
"infercnv-mcp": {
"command": "/home/test/bin/infercnv-mcp",
"args": [
"run"
]
}
}
Run infercnv-server remotely
Refer to the following configuration in your MCP client:
Run it in your server
infercnv-mcp run --transport shttp --port 8000
Then configure your MCP client, like this:
http://localhost:8000/mcp
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:
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