YoussefRagai/analytics-coordinator-mcp-server
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The Analytics Coordinator MCP Server is a bridge layer that facilitates data fetching, transformation, and visualization for AI assistants, enabling seamless integration with Supabase, QuickChart, and MPLSoccer.
Analytics Coordinator MCP Server
A Model Context Protocol (MCP) server that orchestrates Supabase queries and transforms datasets into visualization payloads for other MCP servers such as QuickChart and MPLSoccer.
Purpose
This MCP server provides a bridge layer so AI assistants can fetch data, reshape it into chart or pitch primitives, and optionally render images without writing glue code each time.
Features
Current Implementation
prepare_visual_payload- Converts tabular datasets into QuickChart configs or MPLSoccer primitives.run_pipeline- Executes high-level pipelines (SQL → transform → optional render) and returns either render instructions or base64 images.
Prerequisites
- Docker Desktop with MCP Toolkit enabled
- Docker MCP CLI plugin (
docker mcp) - For Supabase integration:
SUPABASE_URLandSUPABASE_SERVICE_ROLE_KEY(configure via secrets/env) - For QuickChart rendering: optional
QUICKCHART_API_KEY
Installation
See the step-by-step instructions provided with the files.
Usage Examples
In Claude Desktop, you can ask:
- "Convert these Supabase rows into QuickChart line chart config."
- "Run a pipeline that queries Supabase, groups shots, and prepares mplsoccer primitives."
- "Fetch player data, build a bar chart, and render it via QuickChart."
Architecture
Claude Desktop → MCP Gateway → Analytics Coordinator MCP Server → Supabase / QuickChart / Visualization MCPs
Development
Local Testing
# Configure environment for testing
export SUPABASE_URL="https://your-project.supabase.co"
export SUPABASE_SERVICE_ROLE_KEY="service-role-key"
export QUICKCHART_API_KEY="quickchart-key"
# Run directly
python analytics_coordinator_server.py
# Test MCP protocol
echo '{"jsonrpc":"2.0","method":"tools/list","id":1}' | python analytics_coordinator_server.py
Adding New Tools
- Add the function to
analytics_coordinator_server.py - Decorate with
@mcp.tool() - Update documentation and catalog entry
- Rebuild the Docker image
Troubleshooting
Missing Data
- Ensure Supabase SQL returns
columnsandrows - Validate mapping keys exist in dataset
Rendering Errors
- Confirm QuickChart or downstream MCP is accessible
- Check environment variables for required keys
Security Considerations
- Supabase and QuickChart keys read from environment (use Docker secrets)
- No sensitive data logged
- Runs as non-root user inside container
License
MIT License