ChatSpatial
MCP server for spatial transcriptomics analysis through natural language interfaces.
Install / Use
claude mcp add cafferychen777 -- npx -y github:cafferychen777/ChatSpatialIf the server publishes to npm under a different name, use that package instead — check the repo README.
MCP Server
Model Context Protocol server
Quality Score
Category
AI & Machine LearningSupported Platforms
Our assessment of ChatSpatial
ChatSpatial scores 79/100 on our quality scale, 780th of 953 AI & Machine Learning skills we index.
Its MCP Server is 6.4 KB long, split into 6 sections with 3 code examples: a thorough specification that gives an agent plenty to work with.
It has 45 GitHub stars, so there is little community track record yet; judge it on its content.
Maintenance, license and trust
- The repository was last updated 16 days ago, so ChatSpatial is actively maintained.
- Our last check on 2026-10-21 found the source still online.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 92/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-09-24. Automated pattern scan on 2026-09-24. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
ChatSpatial compared with similar skills
All 4 of these similar skills score higher than ChatSpatial; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| ChatSpatial (this skill)by cafferychen777 | 79 | 45 | 16d ago | MCP Server |
| claude-memby thedotmack | 100 | 113.8k | today | CLAUDE.md |
| Agent-Reachby Panniantong | 100 | 109.5k | 1d ago | CLAUDE.md |
| Understand-Anythingby Egonex-AI | 100 | 91.0k | today | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 79.0k | today | CLAUDE.md |
Frequently asked questions
- How do I install ChatSpatial?
- Run
claude mcp add cafferychen777 -- npx -y github:cafferychen777/ChatSpatial. The install tabs above show the steps for each supported agent. - Which AI agents does ChatSpatial work with?
- It is written for Claude Code and Claude Desktop, as a MCP Server file. Other agents that read the same format can often use it too.
- Is ChatSpatial safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is MIT-licensed and scores 92/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is ChatSpatial still maintained?
- The repository was last updated 16 days ago, so ChatSpatial is actively maintained.
Skill content
View source on GitHubChatSpatial
MCP server for spatial transcriptomics analysis via natural language
</div> <p align="center"> <img src="assets/images/overview.jpg" alt="ChatSpatial Overview" width="900"> </p>ChatSpatial replaces ad-hoc LLM code generation with schema-enforced orchestration. Instead of generating arbitrary scripts, the LLM selects tools and parameters from a curated registry, making spatial transcriptomics workflows more reproducible across sessions and clients.
ChatSpatial exposes 20 schema-validated MCP tools that orchestrate 66 spatial transcriptomics methods across 15 analytical categories. The tools are the stable natural-language interface; the methods are the analysis backends selected through tool parameters.
The server implements MCP 2026-07-28 through the official Python SDK v2 and
continues to serve 2025-11-25 clients through SDK-managed protocol negotiation.
STDIO remains the secure local default; Streamable HTTP is available for
explicitly configured HTTP deployments.
Start Here
- Install ChatSpatial — Installation Guide for Python/uv setup, or Docker Guide for the GHCR image
- Configure your MCP client — Configuration Guide
- Run your first analysis — Quick Start
Docker quick start:
docker pull ghcr.io/cafferychen777/chatspatial:v1.3.0
Minimal example prompt:
Load /absolute/path/to/spatial_data.h5ad and show me the tissue structure
If you use Docker, mount host data to /data and prompt with the container path, for example /data/spatial_data.h5ad.
ChatSpatial works with any MCP-compatible client — Claude Code, Claude Desktop, Codex, OpenCode, and other MCP-capable tools.
Capabilities
Current coverage includes 66 methods across 15 analytical categories, exposed through 20 MCP tools. Supports 10x Visium, Xenium, Slide-seq v2, MERFISH, seqFISH.
| Category | Example methods |
|----------|---------|
| Data Loading & Preprocessing | Scanpy I/O, QC, Normalization, HVG, PCA, Neighbors |
| Visualization | Spatial plots, Embedding plots, Gene expression overlays |
| Spatial Domain Identification | SpaGCN, STAGATE, GraphST, BANKSY, AESTETIK, Leiden, Louvain |
| Deconvolution | FlashDeconv, Cell2location, RCTD (spacexr or rctd-py), DestVI, Stereoscope, SPOTlight, Tangram, CARD |
| Cell-Cell Communication | LIANA+, CellPhoneDB, CellChat (cellchat_r), FastCCC |
| Cell Type Annotation | Tangram, scANVI, CellAssign, mLLMCelltype, scType, SingleR |
| Differential Expression | Wilcoxon, t-test, Logistic Regression, pyDESeq2 |
| Trajectory Inference | CellRank, Palantir, DPT |
| RNA Velocity | scVelo, VeloVI |
| Spatial Statistics | Moran's I, Local Moran, Geary's C, Getis-Ord Gi*, Ripley's K, Co-occurrence, Neighborhood Enrichment, Centrality Scores, Local Join Count, Network Properties |
| Enrichment Analysis | GSEA, ORA, Enrichr, ssGSEA, Spatial EnrichMap |
| Spatially Variable Genes | SpatialDE, SPARK-X, FlashS |
| Multi-sample Integration | Harmony, BBKNN, Scanorama, scVI |
| CNV Analysis | InferCNVPy, Numbat |
| Spatial Registration | PASTE, STalign |
Documentation
| Guide | Use this when... | |-------|------------------| | Installation | You need to install ChatSpatial in a Python environment | | Docker | You want a reproducible container runtime or local dependency resolution fails | | Configuration | You need exact MCP client syntax or the runtime path model | | Quick Start | ChatSpatial is installed and you want the first successful analysis | | Concepts | You need to choose an analysis strategy from a biological question | | Examples | You want copy-pasteable natural-language workflow prompts | | Methods Reference | You need canonical tool names, method names, parameters, and defaults | | Troubleshooting | Setup, data loading, or analysis behavior is not working | | Full Docs | You want the complete documentation site |
Citation
If you use ChatSpatial in your research, please cite:
@article{Yang2026.02.26.708361,
author = {Yang, Chen and Zhang, Xianyang and Chen, Jun},
title = {ChatSpatial: Schema-Enforced Agentic Orchestration for Reproducible and Cross-Platform Spatial Transcriptomics},
elocation-id = {2026.02.26.708361},
year = {2026},
doi = {10.64898/2026.02.26.708361},
publisher = {Cold Spring Harbor Laboratory},
URL = {https://www.biorxiv.org/content/early/2026/03/01/2026.02.26.708361},
journal = {bioRxiv}
}
ChatSpatial orchestrates many excellent third-party methods. Please also cite the original tools your analysis used.
Contributing
Documentation improvements, bug reports, and new analysis methods are all welcome. See CONTRIBUTING.md.
<div align="center"> </div> <!-- mcp-name: io.github.cafferychen777/chatspatial -->Related Skills
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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
