Infercnv-MCP
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
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
Related MCP server: Liana-MCP
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-mcpyou can test it by running
infercnv-mcp runrun 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 8000Then configure your MCP client, like this:
http://localhost:8000/mcpđ¤ 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:
This server cannot be deployed
Maintenance
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