Geowire MCP server

GeoWire

Give any AI agent real-world location intelligence in 5 minutes — no API key required.

One interface for place search, directions, and area/market analysis across every map provider.

GeoWire is an open-source geo intelligence gateway that sits between AI agents and map/place data providers (OpenStreetMap, Google, Yelp, Foursquare, US Census, your own data) and exposes them through a single MCP server, REST API, and SDK. One interface for place search, geocoding, directions & distance matrices, and commercial-area analysis (density, ratings, demographics) — with provider fallback, multi-provider merge + dedup, cost budgets, and a policy engine that enforces each provider's caching/attribution terms.

Published on npm — MCP · REST · CLI · SDK all functional. 10 providers, 8 operations.

Honest by design: OpenStreetMap (the zero-key default) is a great

geocoder — strong on place names, addresses, and landmarks — but thin on

category words ("coffee", "pharmacy"), ratings, and hours. For US/Western

commercial data, add a Google, Yelp, or Foursquare key (BYOK) — GeoWire merges

them and tells you which source every field came from. Directions run key-free

on OpenStreetMap routing (OSRM); US demographics come from the Census (free key).

Contents: Why · Quickstart · MCP tools · REST · Anatomy of a response · Config · Providers · Recipes & examples · Roadmap · Architecture

Why GeoWire?

Not a Google replacement — it uses Google. The thing no single provider can do: merge your own store data + Google + OSM into one deduped record, with per-field provenance (your name is authoritative, Google adds ratings, OSM adds coordinates). Real run below:

More than search — location intelligence for agents

Once your agent can find places, it can reason about areas. One analyze_area call turns a point + radius into a commercial-district read — category density, competition, the rating landscape, and (in the US) demographics:

// "Is this a good block for a new café?" — SF, 1 km radius
{ "center": { "latitude": 37.7749, "longitude": -122.4194 }, "radiusMeters": 1000,
  "categories": ["cafe", "restaurant", "bar"] }
// → per-category counts + density/km², avg rating (Google/Yelp), price mix,
//   an activity proxy (Yelp review volume), and Census demographics for the tract.

Same gateway also does directions & distance matrices and travel-time isochrones — key-free via OSRM — so an agent can rank candidates by drive time and answer catchment questions like "what's within a 15-minute drive of this address?" See Recipes.

Quickstart

1. MCP (Claude Desktop / Cursor) — 30 seconds

Add this to your MCP client config (e.g. Claude Desktop claudedesktopconfig.json):

{
  "mcpServers": {
    "geowire": { "command": "npx", "args": ["-y", "@geowirehq/mcp"] }
  }
}

Shortened. The full README is on GitHub.