An MCP server that enables scRNA-Seq analysis through natural language, providing tools for data preprocessing, clustering, and biological visualization. It supports both predefined function execution and a flexible code mode powered by a Jupyter backend for automated single-cell transcriptomics workflows.
Provides a natural language interface for scRNA-Seq analysis using the Scanpy library, supporting operations such as data preprocessing, clustering, and visualization. It enables AI agents and clients to perform complex single-cell transcriptomics workflows through the Model Context Protocol.
An MCP server that enables single-cell RNA sequencing analysis through natural language, supporting data processing, visualization, and analysis tasks without requiring coding knowledge.
Provides a natural language interface for single-cell RNA-Seq analysis using the decoupleR framework. It enables users to perform biological pathway inference, data clustering, and visualization through MCP-compatible AI clients.
Enables deep probabilistic analysis of single-cell omics data using scvi-tools through natural language. Supports SCVI for scRNA-seq analysis, SCANVI for cell type annotation, TOTALVI for multi-modal RNA/protein data, and PEAKVI for scATAC-seq analysis.
Enables natural language interface for single-cell RNA-Seq analysis using Liana. Supports reading/writing scRNA-Seq data, cell-cell communication analysis, and visualization through circle plots and dotplots.
