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glassmap.clyeh.xyz

glassmap.clyeh.xyz

live Unverified (seed import) Travel & Events 15 tools mixed implementation

An agent-native web map: WebMCP turns the map canvas into a semantic surface.

First seen 2026-11-05 · Last seen 2026-11-05 · Source: webmcp.com

Answer 7 · Act 8 · Transact 0 · Score: Not yet scored

Tool inspector

compare_areas

answer imperative

Compare two places in one call: how many features of each category are within radius_m of a, how many are within radius_m of b, and the nearest one of each category on each side. Both places are given the same way as anywhere else - a feature id, a place name such as "Zhongshan Station", or a coordinate - and both are counted with exactly the filter find_features uses, so the numbers match what a per-category search would return. Read "summary" out; use by_category to reason and its feature ids to act (select_features, set_map_view). A point of interest tagged as two categories - a bakery that also serves fast food - is counted under each of them, exactly as both of their find_features queries return it, so by_category can add up to slightly more than total, which counts places. This replaces one find_features call per category per place.

Input schema

PropertyTypeRequiredDescription
a — yes The first place: a feature id from an earlier call, a place name such as "Daan Park Station", or an explicit coordinate. If a name matches several places nothing is counted and the answer lists the candidates.
b — yes The second place, in any of the same three forms as a.
radius_m number no How far around each place to count, in metres (default 800, a comfortable walk; at most 10000). The same radius is used on both sides - that is what makes the two counts comparable. A larger radius is refused rather than quietly narrowed.
categories array no Which categories to count. Always in memory: mrt_station, park, school, supermarket, listing, district. Points of interest, fetched for the whole city the first time you name one and kept for the rest of the session: restaurant, cafe, fast_food, bakery, bar, convenience, pharmacy, clinic, hospital, place_of_worship, bank, hotel, parking, bicycle_rental, library, museum, post_office, police. Naming a category is how you search it - there is no way to search all of them at once. Omit this and the answer counts mrt_station, park, school, supermarket, listing plus the points of interest fetched earlier in this session, and lists what it did not count under unsearched_categories with how many exist city-wide; district is never counted, because it is a property of a place rather than something near it.
Raw JSON schema
{
  "type": "object",
  "properties": {
    "a": {
      "description": "The first place: a feature id from an earlier call, a place name such as \"Daan Park Station\", or an explicit coordinate. If a name matches several places nothing is counted and the answer lists the candidates.",
      "anyOf": [
        {
          "type": "string",
          "description": "A feature id, or the name of a station, park or district. A name needs the base data the page loads on open; before that it answers \"map data not ready\" rather than guessing, and asking again works."
        },
        {
          "type": "object",
          "properties": {
            "lng": {
              "type": "number",
              "minimum": -180,
              "maximum": 180,
              "description": "Longitude in degrees."
            },
            "lat": {
              "type": "number",
              "minimum": -90,
              "maximum": 90,
              "description": "Latitude in degrees."
            }
          },
          "required": [
            "lng",
            "lat"
          ],
          "additionalProperties": false,
          "description": "Explicit coordinate."
        }
      ]
    },
    "b": {
      "description": "The second place, in any of the same three forms as a.",
      "anyOf": [
        {
          "type": "string",
          "description": "A feature id, or the name of a station, park or district. A name needs the base data the page loads on open; before that it answers \"map data not ready\" rather than guessing, and asking again works."
        },
        {
          "type": "object",
          "properties": {
            "lng": {
              "type": "number",
              "minimum": -180,
              "maximum": 180,
              "description": "Longitude in degrees."
            },
            "lat": {
              "type": "number",
              "minimum": -90,
              "maximum": 90,
              "description": "Latitude in degrees."
            }
          },
          "required": [
            "lng",
            "lat"
          ],
          "additionalProperties": false,
          "description": "Explicit coordinate."
        }
      ]
    },
    "radius_m": {
      "type": "number",
      "exclusiveMinimum": 0,
      "maximum": 10000,
      "description": "How far around each place to count, in metres (default 800, a comfortable walk; at most 10000). The same radius is used on both sides - that is what makes the two counts comparable. A larger radius is refused rather than quietly narrowed."
    },
    "categories": {
      "type": "array",
      "minItems": 1,
      "items": {
        "type": "string",
        "enum": [
          "mrt_station",
          "park",
          "school",
          "supermarket",
          "listing",
          "district",
          "restaurant",
          "cafe",
          "fast_food",
          "bakery",
          "bar",
          "convenience",
          "pharmacy",
          "clinic",
          "hospital",
          "place_of_worship",
          "bank",
          "hotel",
          "parking",
          "bicycle_rental",
          "library",
          "museum",
          "post_office",
          "police"
        ]
      },
      "description": "Which categories to count. Always in memory: mrt_station, park, school, supermarket, listing, district. Points of interest, fetched for the whole city the first time you name one and kept for the rest of the session: restaurant, cafe, fast_food, bakery, bar, convenience, pharmacy, clinic, hospital, place_of_worship, bank, hotel, parking, bicycle_rental, library, museum, post_office, police. Naming a category is how you search it - there is no way to search all of them at once. Omit this and the answer counts mrt_station, park, school, supermarket, listing plus the points of interest fetched earlier in this session, and lists what it did not count under unsearched_categories with how many exist city-wide; district is never counted, because it is a property of a place rather than something near it."
    }
  },
  "required": [
    "a",
    "b"
  ],
  "additionalProperties": false
}

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