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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.

Why PlaceRoot

It is the only keyless MCP server that does real graph routing over global open map data. isochrone and route walk an actual street graph built from Overture's transportation segments — not a straight-line approximation — anywhere on Earth, with no key, no signup, and no per-call quota. All 29 tools work that way.

Every one of those 29 tools declares MCP annotations — closed-world, plus a human-readable title, and readOnlyHint: true on the 28 that are pure lookups — so a client can tell before it prompts you which calls touch nothing. The one exception is honest about itself: render_map writes an HTML file, so it declares readOnlyHint: false. Keyless and annotated is a combination the field mostly hasn't shipped. Honest caveat: Claude Code does not gate its permission prompts on readOnlyHint (it uses its own classifier), so the practical win is with clients that do, such as Codex CLI and Copilot-class agents — plus spec hygiene everywhere else.

PlaceRoot also speaks the MCP 2026-07-28 revision's listing cache hints: tools/list (and the prompt and resource listings) come back with ttlMs: 86400000 and cacheScope: "public". Our listings are frozen at build time — nothing at runtime can change them — so a client is free to reuse them for a day instead of re-reading a ~12k-token schema surface every session. Clients that speak an older revision are unaffected: those fields did not exist before 2026-07-28, and the response they get is byte-identical to what it was.

What it deliberately does not do, because Overture's open data does not carry it:

  • No live traffic. Routing is free-flow; durations do not reflect current conditions.
  • No opening hours. Places carry categories, brands and contacts, not schedules.
  • No ratings or photos. There is no review corpus and no imagery behind these answers.

If a question needs one of those three, a commercial maps API is the right tool. For where things are, what is around them, and what is reachable from them, PlaceRoot answers without a key.

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

29 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
infrastructure_at Infrastructure near a point, nearest first — filter by subtype/infra_class (e.g. bridge, tower) to see past the street furniture
water_near Water near a point, nearest first — is this waterfront, how far to the nearest river/canal/lake; filter by subtype/water_class
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)
address_at Point → the nearest street addresses (number, street, unit, postcode), with an explicit note when the country is outside Overture's 39-country address coverage
geocode_address Street address → coordinates: "1600 Amphitheatre Parkway, Mountain View" — city-bounded, deduplicated to distinct number+street, nearest first
gers_lookup Any GERS id → the entity it names (place, division, or building), what it's inside, and the building at its point
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; include_path=true adds the simplified route polyline
places_along_route Places on the way from A to B: corridor search along the route, with each result's detour and how far along it sits
optimize_route Best order to visit 2–10 stops, solved exactly over the street graph — order, per-leg distance/duration, and totals
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

Workflow prompts

Three MCP prompts ship with the server: canned multi-tool workflows that encode which tool to call first, what to do with its output, and what the answer should look like. In Claude Code they appear as slash commands; Claude Desktop and Cursor surface them in their own prompt pickers.

Prompt Arguments Workflow
/mcp__placeroot__site_selection business_type, area search_categoriesgeocodesummarize_areacompare_areasfind_places + within_distance → one ranked recommendation
/mcp__placeroot__compare_neighborhoods area_a, area_b geocode/resolve_place + admin_lookupsummarize_area ×2 → compare_areassummarize_buildings → a small difference table
/mcp__placeroot__plan_errands stops, start (optional) geocode_batchdistance_matrixroute per leg → optional places_along_route → an ordered run with per-leg distance and duration
/mcp__placeroot__site_selection bike repair shop | Portland, Oregon

Prompts cost zero tokens in tools/list — a client fetches them only on prompts/list, and only materializes one when you invoke it. A test asserts tools/list is byte-identical with and without them registered, so adding a workflow here can never grow the context every conversation pays for.

They are also registered under every PLACEROOT_TOOLS selection, including subsets that drop tools a prompt names — a workflow is still worth reading when one step is unavailable, and it costs a subset install nothing. When the active selection excludes a referenced tool, the rendered prompt ends with a note naming it and telling the agent to route around the gap rather than to attempt a call that would fail.

Resources

Two MCP resources expose the server's argument-free lookups as attachable context, so you can pin them into a conversation without spending a tool call:

Resource Contents
placeroot://data-version The resolved Overture release, its date, and how it was resolved (discovery, env override, or the pinned fallback). Same values the data_version tool returns — one shared code path, so they cannot drift.
placeroot://categories Summary of the place-category taxonomy: all 22 top-level categories with how many slugs sit under each, plus how to get an exact slug. ~530 tokens — a summary, not the 2,117-slug CSV, which stays behind search_categories.

In Claude Code they auto-complete as @-mentions:

@placeroot:placeroot://data-version
@placeroot:placeroot://categories

Claude Desktop and Cursor list them in their own attachment pickers.

Like prompts, resources are registered under every PLACEROOT_TOOLS selection: they never appear in tools/list, so gating them would save a subset install nothing. A test asserts tools/list is byte-identical with and without them registered.

Loading fewer tools (PLACEROOT_TOOLS)

All 29 tool schemas cost roughly 13.2k tokens of every conversation's context, paid before the agent asks anything — about the cost of 100 median answers. Most installs use a slice of that surface, so PLACEROOT_TOOLS selects which tools get registered. Unselected tools are never registered and never appear in tools/list.

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

The value is a comma-separated list of profile names, tool names, or both — the union of everything named:

PLACEROOT_TOOLS Tools Schema tokens Saved
unset / all (default) 29 ~13,160
search 13 ~6,170 53%
core 10 ~5,280 60%
routing 6 ~2,890 78%
analysis 9 ~3,240 75%
geometry 3 ~850 94%
progressive 3 (all 29 reachable) ~550 96%
  • corefind_places, geocode, reverse_geocode, place_details, resolve_place, search_categories, summarize_area, route, places_along_route. The single-purpose tools that answer most spatial questions; no batch siblings, no buildings/land-use, no rendering. search_categories is in for its own reason: find_places' category filter takes Overture taxonomy slugs, and a wrong slug comes back as zero results plus a note to look the slug up — a dead end without the lookup tool to call.
  • search — the find/name/identify family: find_places, place_details, geocode, resolve_place, reverse_geocode, their *_batch siblings, address_at, geocode_address, search_categories, and gers_lookup.
  • routingroute, isochrone, distance_matrix, within_distance, optimize_route.
  • analysissummarize_area, summarize_buildings, compare_areas, buildings_at, land_use_at, infrastructure_at, water_near, admin_lookup.
  • geometrysimplify_geometry, render_map.
  • progressive — not a slice of the surface but a door to it: placeroot_capabilities() returns a ~1,000-token catalog of all 29 tools (name, one-liner, argument list), and placeroot_call(tool, args) runs any of them and returns the tool's own answer unchanged. For the install that wants everything available without paying 13.2k tokens for it in every conversation — profiles need you to know up front which tools you want; this doesn't. One extra round trip when the agent needs the catalog. It replaces the surface rather than adding to it, so it has to stand alone: PLACEROOT_TOOLS=progressive,core fails at startup rather than registering both.

data_version is registered under every profile: it is ~230 tokens and the only way an agent can tell which Overture release backs its answers.

Profiles may overlap, and a list may mix them with bare tool names — PLACEROOT_TOOLS=routing,find_places or PLACEROOT_TOOLS=find_places,geocode,route. A name that is neither a profile nor a tool fails at startup with the list of valid names, rather than quietly falling back to loading everything. The server logs one line at startup naming what it registered (registered 10 of 29 tools (PLACEROOT_TOOLS=core)), so a selection that didn't apply — an empty value, a variable that never reached the process — is visible rather than silently the full 29.

Design notes

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

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