What does Infercnv-MCP do?
It provides a natural language interface to the infercnvpy library, enabling users to perform CNV inference from scRNA‑Seq data, including preprocessing, scoring, and visualization, through any MCP‑compatible client.
@scmcphub
基本情報
MCP server for CNV analysis using infercnv
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ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
Infercnv-MCP is a natural language interface for Copy Number Variation (CNV) inference from single-cell RNA-Seq (scRNA-Seq) data, powered by the infercnvpy library and the Model Context Protocol (MCP). It provides modules for reading/writing scRNA-Seq data, preprocessing, CNV inference and scoring, and plotting (chromosome heatmaps, UMAP, t-SNE). The tool targets researchers and agent developers who want to perform or integrate CNV analysis using natural‑language commands.
Install the package from PyPI (pip install infercnv-mcp), then run it either locally (infercnv-mcp run) or as a remote HTTP server (infercnv-mcp run --transport shttp --port 8000). Configure your MCP client (e.g., Cherry Studio, Cline, Agno) with the appropriate command or endpoint.
It provides a natural language interface to the infercnvpy library, enabling users to perform CNV inference from scRNA‑Seq data, including preprocessing, scoring, and visualization, through any MCP‑compatible client.
Install it via pip: `pip install infercnv-mcp`. After installation, you can test the server by running `infercnv-mcp run`.
Yes. Start the server with `infercnv-mcp run --transport shttp --port 8000`, then point your MCP client to `http://localhost:8000/mcp` (or the appropriate URL).
The IO module handles reading and writing scRNA‑Seq data; specific file formats are not detailed, but it loads gene position information for downstream analysis.
It is built for researchers who want to infer CNVs from scRNA‑Seq data using natural language, and for agent developers who need to embed CNV analysis into their applications.

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