ChatSpatial¶
MCP server for spatial transcriptomics analysis via natural language.
Analyze your spatial data from any MCP-compatible client. No coding required.
ChatSpatial exposes 20 schema-validated MCP tools. Those tools orchestrate 65 spatial transcriptomics methods across 15 analytical categories; the tools are the user-facing interface, and the methods are selected through tool parameters.
20 MCP tools orchestrating 65 methods across 15 analytical categories. Supports 10x Visium, Xenium, Slide-seq, MERFISH, and more.
Choose Your Path¶
- New to ChatSpatial:
- Already running ChatSpatial:
Concepts for method selection, Examples for prompt recipes, and Methods Reference for exact parameters.
- Something failed:
Start with Troubleshooting, then use Frequently Asked Questions for short answers and pointers.
- Contributing:
Use Contributing to find the right contribution path.
Getting Started¶
Set up the environment
Install ChatSpatial and prepare your Python environment.
Your first analysis
Load data and start analyzing with natural language.
Run without local dependency resolution
Pull the GHCR image, mount data, and configure MCP.
Understand the methods
When to use which method and why.
See what’s possible
Natural language commands for every analysis type.
Reference¶
MCP tools, supported methods, parameters, and defaults
MCP client configuration
External dataset registry and fetch workflow
Contributor entry point for docs and code changes
Support¶
Troubleshooting — Common issues and solutions
Frequently Asked Questions — Frequently asked questions
GitHub Issues — Report bugs