A Centralized MCP Server for Fetching Data from Many Countries' Govs
View on GitHub ↗A Model Context Protocol (MCP) server that lets AI agents search, explore, and fetch open datasets from official government data portals. One unified tool interface across the United States, United Kingdom, Canada, and Australia — with per-portal quirks (API migrations, auth walls, bilingual metadata, stale DataStore flags) absorbed behind a common adapter layer.
Built for the typical agent workflow: "Is there a government dataset for X?" → find candidates → inspect the files → preview rows or grab a download link and move on.
- Four national portals, one interface. US (data.gov v4 / DCAT), UK (data.gov.uk / CKAN), Canada (open.canada.ca / CKAN), Australia (data.gov.au / CKAN + DataStore). - Token-frugal by design. Descriptions are HTML-stripped and truncated, search results are compact summaries, and large files are never inlined by accident. - Row-level preview. Uses CKAN DataStore where available (Australia), and transparently falls back to reading the head of CSV/TSV files everywhere else. - Agent-friendly failure modes. Errors are returned as actionable text ("use getdownloadlink instead", "retry with datasetid", "available portals: …") — never raw tracebacks. - Extensible registry. Adding another CKAN-based portal is a single config entry; non-CKAN portals plug in via a small adapter class. - Dual transport. stdio for local clients (Claude Desktop etc.), stateless streamable-http for serverless deployment (Google Cloud Run).
From the project README.
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An OKF-backed Model Context Protocol (MCP) server delivering persistent long-term memory and SQLite FTS5 search for AI agents.
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