Open Census MCP Server
About
Access and query U.S. Census demographic data using natural language.
Details
- Author
- brockwebb
- Categories
- Database
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Setup
Install Open Census MCP Server in your MCP client (Claude Desktop, Cursor, Windsurf, and others).
Repository: https://github.com/brockwebb/open-census-mcp-server
Follow the installation instructions in the repository README, then restart your MCP client.
Access and query U.S. Census demographic data using natural language.
This is anindependent, open-source experiment. It isnotaffiliated with, endorsed by, or sponsored by the U.S. Census Bureau or the Department of Commerce.
Data retrieved through this project remains subject to the terms of the original data providers (e.g., Census API Terms of Service).
An AI-powered statistical consultant for U.S. Census data. Ask questions in plain English, get accurate demographic data with proper statistical context, methodology guidance, and fitness-for-use caveats.
The insight:Census data has a pragmatics problem, not a search problem. Knowing WHICH data to use and HOW to interpret it matters more than finding it. This system encodes statistical consulting expertise into the AI interaction layer.
🔬Active Research & Rebuild— v3 architecture in progress. Seedocs/lessons_learned/for the v1/v2 journey.
Census data influences billions in policy decisions, but accessing it effectively requires specialized knowledge. This project aims to make America's most valuable public dataset as easy to use as asking a question — with the statistical rigor of a professional consultant.
The opportunity:Every city council member, journalist, nonprofit director, and curious citizen should be able to fact-check claims and understand their communities with the same ease an eighth-grader uses a search engine. The data is public. The expertise to use it properly shouldn't be gatekept by technical complexity.
Pure Python MCP server with pragmatic rules engine. No R dependency.
- Pragmatic Rules Layer:Fitness-for-use constraints (MOE thresholds, coverage bias, temporal validity, source selection)
- Census API Integration:Direct Python calls to Census Bureau APIs
- Knowledge Base:Methodology documentation for RAG-enhanced guidance
Details:docs/architecture/(coming soon)
docs/ # Systems engineering documentation requirements/ # ConOps, SRS architecture/ # System architecture decisions/ # ADRs, trade studies design/ # Detailed design verification/ # V&V, evaluation results lessons_learned/ # Project narrative & lessons knowledge-base/ # Source docs & pragmatic rules source-docs/ # Census methodology PDFs (gitignored) rules/ # Extracted pragmatic rules methodology/ # Processed methodology content src/ # MCP server source code tests/ # Evaluation harness & unit tests scripts/ # Build & utility scripts
- U.S. Census Bureau— for collecting and maintaining vital public data
- Kyle Walker—Analyzing US Census Datatextbook as knowledge base source
- Anthropic— Model Context Protocol enabling AI tool integration
- Domain expertise from Census data veterans
- Statistical methodology review
- Evaluation test cases (real-world query scenarios)
MIT License - seeLICENSEfile for details.
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