Server Deployment Guide

Deploy ChatSpatial on a server for team-wide access to spatial transcriptomics analysis.

MCP Server Deployment

ChatSpatial implements the Model Context Protocol (MCP) with two transport modes:

Local Mode (stdio)

For Claude Desktop and local clients:

# Install ChatSpatial
pip install -e ".[full]"

# Run in stdio mode (default)
python -m chatspatial

Remote Mode (SSE)

For remote access and HTTP-based clients:

# SSE mode with HTTP/WebSocket support
python -m chatspatial server --transport sse --port 8000 --host 0.0.0.0

Note: Use with mcp-remote proxy for Claude Desktop remote connections:

# Client-side proxy setup
npx mcp-remote http://your-server:8000/mcp/

Requirements

  • Python 3.10-3.12 (MCP requires Python 3.10+)
  • 64 GB RAM recommended for large datasets
  • Fast SSD storage
  • Network access for team

Configuration

Create config.yaml for server settings:

server:
  host: 0.0.0.0
  port: 8000
  max_connections: 10
  
data:
  cache_dir: /data/chatspatial_cache
  max_dataset_size: 10GB

Security Notes

  • Use VPN or internal network only
  • Add authentication if exposing to internet
  • Regular backups of analysis results

Getting Help

  • GitHub Issues for deployment questions
  • Check logs in /var/log/chatspatial/

Next: Configuration Guide