Grounds AI agents in Overture Maps open data — compact answers, no API key.
io.github.chuofringer/placeroot MCP Server
The io.github.chuofringer/placeroot Model Context Protocol (MCP) server grounds AI agents in Overture Maps open data. It provides compact answers and is designed to work without an API key, leveraging geospatial and geocoding capabilities. The project is tagged for routing and GIS workflows.
🛠️ Key Features
Ground AI agents in Overture Maps open data
Compact answers
No API key requirement
🚀 Use Cases
Geocoding with Overture Maps open data
Geospatial agent support using MCP
Routing and GIS-related agent tasks
⚡ Developer Benefits
Works with Model Context Protocol (mcp)
Includes tooling support for llm-tools
Integrates well with geospatial pipelines (topics include gis, routing)
⚠️ Limitations
Description excerpt does not specify supported languages, MCP tools, or tool count.
PlaceRoot grounds AI agents in open map data. It's an MCP server that answers spatial questions — what's nearby, what's in this neighborhood, how do I get there — from Overture Maps open data. 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.
🗺️ Real routing, zero keys.route and isochrone walk an actual street graph built from Overture's transportation segments — not a straight-line guess — anywhere on Earth.
🚶 Reachability-filtered search.find_places(..., within={"minutes": 15, "mode": "walk"}) keeps only results truly inside the street-graph walk/cycle/driveshed — not a radius that guesses at it, and not a second call to intersect a polygon yourself.
🏙️ Rich, filterable place data. Category, brand, confidence, operating status, contactability — 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 a guessed radius circle.
⚡ Zero setup. Reads Overture's public data directly — no key, no database, nothing to install beyond the server itself.
Quick start
Run it straight from PyPI or npm — no install step:
bash
uvx placeroot # stdio MCP server
uvx placeroot --http # HTTP endpoint at http://127.0.0.1:8321/mcp
How far to walk from A to B? What's reachable in 15 minutes? Best order for 6 stops? Which streets did this GPS trace actually take?
🗺️ Geometry & maps
render_map, simplify_geometry
Show me this result as an interactive map
It also ships seven workflow prompts (site selection, neighborhood comparison, errand planning, should I live here, get to know my city, verify listing claims, plan area visit) and three attachable resources — and a PLACEROOT_TOOLS setting to load only the tool profiles you need, cutting schema overhead by up to 95%.
Open data has honest limits: no live traffic, no opening hours, no ratings or photos — what PlaceRoot deliberately doesn't do. For everything else about where things are and what's reachable from them, it answers without a key.
Why PlaceRoot
It's the only keyless MCP server doing real graph routing over global open map data — with every tool declaring proper MCP annotations so clients know which calls are read-only before prompting you. Stable GERS ids let agents hold onto places across turns; local caching makes repeat queries answer in milliseconds and keeps working offline; and the whole thing is self-hostable end to end.
Overture's places theme is derived from business listings, which makes it strong on businesses and thin on the places a family goes on a Saturday — playgrounds, neighbourhood parks, dog parks, beaches. Those features aren't missing from Overture, though; they're in a different theme. Overture's base theme is a direct conflation of OpenStreetMap, and PlaceRoot already queries it for land_use_at and infrastructure_at. The places tools read it too, by default.
Nothing is downloaded, built, or hosted — it's one more live scan of the same public Overture release, and it roughly 2.5xes playground coverage (1,552 vs 674 across New York City in release 2026-07-22.0, with 1,013 of them more than 150 m from any places-theme playground). Every places tool answers from both at once, with no other change: same tools, same response shape, same category filters.
The cost is a second dataset scan per places query (cached like everything else), and these rows carry no confidence or operating_status and are often unnamed — an unnamed playground comes back with name: null rather than being dropped. If you'd rather have the latency than the coverage:
bash
export PLACEROOT_RECREATION_LAYER=0
data_version reports the layer whenever it's active. Full details, including why live Overpass queries and raw OSM Parquet were measured and rejected: docs/RECREATION.md.
Development
bash
uv sync# install dev dependencies
uv run pytest # offline test suite
uv run ruff check .
PlaceRoot runs on your machine — no account, no API key, no sign-up. It has no telemetry and sends nothing to us; the only network traffic is your own queries going straight to Overture Maps' public data on AWS S3 (or a mirror you configure). Full details: placeroot.dev/privacy.html.
License and attribution
The code is MIT. The data it queries is the Overture Maps public release, licensed per theme — places under CDLA-Permissive-2.0; the OSM-derived themes (divisions, transportation, base) under ODbL, which asks for attribution on anything user-facing you build from them: