Provides deep probabilistic analysis tools for single-cell omics data using scvi-tools, including SCVI for scRNA-seq modeling, SCANVI for cell type annotation, TOTALVI for RNA/protein analysis, and PEAKVI for scATAC-seq analysis.
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., "@scvi-tools MCP ServerExtract latent representation from my scRNA-seq data with batch correction"
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.
scvi-tools MCP Server
An MCP (Model Context Protocol) server for deep probabilistic analysis of single-cell omics data using scvi-tools with natural language!
π― What can it do?
SCVI: Deep generative modeling for scRNA-seq
Latent representation extraction
Normalized expression
Differential expression analysis
Batch effect correction
SCANVI: Semi-supervised cell type annotation
Transfer learning from labeled to unlabeled cells
Cell type prediction
TOTALVI: Joint RNA and protein (CITE-seq) analysis
Multi-modal integration
Protein expression denoising
PEAKVI: scATAC-seq analysis
Chromatin accessibility
Differential accessibility
π¦ Installation
cd /path/to/scvi-mcp
python3 -m venv venv
source venv/bin/activate
pip install -e .π Quick Start
scvi-mcp run --data /path/to/data.h5adπ§ Configuration for Claude Desktop
{
"mcpServers": {
"scvi": {
"command": "/path/to/scvi-mcp/venv/bin/python",
"args": ["-m", "scvi_mcp", "run", "--data", "/path/to/data.h5ad"]
}
}
}π οΈ Available Tools (22 tools)
SCVI (8 tools)
scvi_setup_anndata, scvi_create_model, scvi_train_model
scvi_get_latent_representation, scvi_get_normalized_expression
scvi_differential_expression, scvi_save_model, scvi_load_model
SCANVI (4 tools)
scanvi_setup_anndata, scanvi_create_model
scanvi_from_scvi_model, scanvi_predict
TOTALVI (3 tools)
totalvi_setup_anndata, totalvi_create_model
totalvi_get_protein_foreground_prob
PEAKVI (3 tools)
peakvi_setup_anndata, peakvi_create_model
peakvi_differential_accessibility
Common (2 tools)
scvi_get_elbo, scvi_get_reconstruction_error
π Example Usage
Basic SCVI workflow:
1. "Setup my data for SCVI analysis with batch correction"
2. "Create an SCVI model with 10 latent dimensions"
3. "Train the SCVI model"
4. "Extract the latent representation and save it to X_scVI"
5. "Run differential expression between cell types"SCANVI cell type annotation:
1. "Setup SCANVI with cell_type labels, mark Unknown as unlabeled"
2. "Create SCANVI model from my trained SCVI model"
3. "Train SCANVI and predict cell types"π License
MIT License