Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Schema-enforced spatial transcriptomics analysis with 20 tools and 67 methods via MCP
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Pick the AI app you use, then copy the settings.
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"chatspatial": {
"command": "uvx",
"args": [
"chatspatial",
"server"
]
}
}
}Run this in your terminal
claude mcp add chatspatial -- uvx chatspatial serverPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"chatspatial": {
"command": "uvx",
"args": [
"chatspatial",
"server"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"chatspatial": {
"type": "stdio",
"command": "uvx",
"args": [
"chatspatial",
"server"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
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Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 9, 2026
The registry name was verified with the GitHub account cafferychen777, which owns the repo
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This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
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It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (1.6.0) reached the registry 20 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, MCP Tennis Match Data
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MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
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MCP server for spatial transcriptomics analysis via natural language
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 67 spatial transcriptomics methods across 13 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.
Install uv once, then register ChatSpatial without creating or managing a Python environment:
Codex:
codex mcp add chatspatial -- uvx --from chatspatial chatspatial server
Claude Code:
claude mcp add --scope user chatspatial -- \
uvx --from chatspatial chatspatial server
uvx creates an isolated environment on first launch and reuses its cache on later launches. Restart the MCP client after adding the server.
The command above installs the standard runtime. To make all 15 composable Python method families available in the same isolated MCP environment, use:
uvx --from 'chatspatial[full]' chatspatial server
full includes CellRank, FastCCC, the maintained spatial-domain and registration backends, annotation, enrichment, and the other portable Python families. R bridges, AESTETIK, and rctd-py remain separate because they have system, platform, or large-runtime requirements. See the installation guide before enabling those families.
Then:
Docker quick start:
docker pull cafferyyang777/chatspatial:latest
Minimal example prompt:
Load /absolute/path/to/spatial_data.h5ad and plot gene expression at the spatial coordinates
The Quick Start provides a downloadable sample and a Leiden workflow that runs with the standard installation. Its sample has spatial coordinates but no H&E image. SpaGCN requires the optional spatial-domains extra.
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.
Current coverage includes 67 methods across 13 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, marker-score and threshold rules |
| 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 |
| Guide | Use this when... |
|---|---|
| Installation | You need optional methods or a persistent 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 |
Each release publishes a reproduction image under the -repro tag. It re-executes the DLPFC spatial-domain and OSCC CARD deconvolution tool calls recorded during the manuscript experiments, without calling any LLM, and compares the results with the reported values:
docker run --rm -v "$PWD/out:/outputs" \
cafferyyang777/chatspatial@sha256:ac3ba1ed8235c3d53ca72005d8ad2556cac007f5ddb932ae3e1d1241fa2cf9d8 \ chatspatial-reproduce
reproducibility/ contains the image definition and describes what it checks. The experiment and analysis scripts for the manuscript are in ChatSpatial-Reproducibility.
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.
Documentation improvements, bug reports, and new analysis methods are all welcome. See CONTRIBUTING.md.