PlaceRoot

Ground AI agents in open map data.

PlaceRoot is an MCP server that answers spatial questions from Overture Maps — no API key, no signup, no vendor platform.

  • Answers, not data dumps. Every tool returns compact, ranked results sized for an agent's context window — never a raw GeoJSON dump.
  • Rich, filterable place data. Category, brand, confidence, operating status, contactability — all queryable, sourced from Overture's open dataset (contributed by Meta, Uber, TomTom, and others).
  • Boundary-accurate. Search inside a named place's real administrative polygon, not just a guessed radius circle.
  • Zero setup. Reads Overture's public data directly — nothing to install beyond the server itself, no key, no database.

Quick start

Add to Claude Desktop / Claude Code:

{
  "mcpServers": {
    "placeroot": {
      "command": "uvx",
      "args": ["placeroot"]
    }
  }
}

(npx placeroot also works, if you'd rather use the npm launcher: set "command": "npx".)

Or run it directly:

uvx placeroot             # stdio MCP server
uvx placeroot --http      # HTTP endpoint at http://127.0.0.1:8321/mcp

What it can do

22 tools, all returning compact, budgeted answers. Several single-item tools have a *_batch sibling that collapses many calls into one round-trip.

Tool Answers
find_places Named places near a point or inside a named area / division polygon, nearest first — filter by category, brand, confidence, operating status, or has-website / has-phone
summarize_area What's in an area: total places and top categories
compare_areas 2–5 areas side by side: category mix, density, and what differs most
within_distance Is the nearest matching place within N meters of a point?
distance_matrix Straight-line distances between many origins and destinations at once
place_details One place in full: addresses, contacts, brand, sources, confidence
admin_lookup The admin hierarchy containing a point: neighborhood up to country
summarize_buildings Building stock in an area: count, footprint area, height and use mix
buildings_at Nearest building footprints to a point
land_use_at What kind of land is this: land use and land cover classification at a point
geocode Free-text place name → ranked candidates with coordinates and admin context (geocode_batch for many at once)
resolve_place Free-text place reference → stable ids an agent can hold onto across turns (resolve_place_batch)
reverse_geocode Point → nearest address plus its containing admin areas (reverse_geocode_batch)
search_categories Free text → the right Overture category slug to filter find_places by
isochrone The area reachable within N minutes on foot, bike, or car
route Shortest-path distance and duration between two points, on foot, bike, or car
render_map Any result → a self-contained interactive HTML map
simplify_geometry Any geometry → simplified to fit a token budget
data_version Which Overture release the answers are drawn from

Why

Agents are bad at maps. Existing map tools either require vendor API keys or return payloads far too large for a context window. PlaceRoot's rule: every answer fits in a couple of thousand tokens, and anything bigger comes back as a summary.

A few things that set it apart:

  • Stable place ids. Every place carries its Overture GERS id, so an agent can hold onto a place across turns and look it up again later instead of re-searching.
  • Built-in geocoding. Place-name lookup works out of the box — no third-party geocoding service involved.
  • Fast repeat queries. Frequently used data is cached locally, so repeat questions answer in milliseconds and keep working offline.
  • Self-hostable end to end. Run it locally, serve it over HTTP, or point it at your own copy of the data — no dependency on anyone else's service.

Development

uv sync           # install dev dependencies
uv run pytest     # offline test suite
uv run ruff check .

Docs

License

MIT

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (0.8.0)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for chuofringer from gravatar.com chuofringer

Credits

Author: Vibe Mapper

License expression

MIT
View SPDX License List

Requires

Python >=3.11

Tags

ai-agents duckdb geospatial mcp openstreetmap overture-maps

Classifiers

Report project as malware

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