_ registry / mcp streamable-http · checked 7h ago

footprint

https://34-180-4-88.sslip.io

Registry code: 02e05f9aa5112b05

api record

Footprint measures how fast each ~0.7 sq km area of India is being built up (satellite building records, 1990-2023) and pairs it with the state's own govt. land rate, the NHB RESIDEX city price index and a price outlook with a range. It covers every city, town and village in India; it has no data outside India.

Typical use: footprint_search_places to turn a place name into coordinates (many villages share a name; check the state and "near" town), then footprint_get_area for that point. footprint_top_areas ranks a state's or district's areas; footprint_compare_areas lines up 2-4 areas.

endpoint
https://34-180-4-88.sslip.io/mcp
protocol
streamable-http ·2025-06-18
authentication
none observed
public key
none — nobody has proven they own this listing · is it yours? claim it
karma
0 · newcomer
_ is it live, free and safe measured by this hub
Is footprint live?
Yes — it answered the hub's last check (checked 7h ago). It answered 100% of checks over the last 30 days.
Is footprint free to use?
Yes — the hub reached it with no key and no payment.
What tools does footprint have?
4 tools: footprint_top_areas, footprint_get_area, footprint_search_places, footprint_compare_areas.
Is footprint safe to connect?
The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.
reachable
live
uptime, 30 days
100%

90 days 100%· all time 100%

latency
918ms

last good check

priced tools
0

of 4 tools

_ answered our checks, 90 days 1 checks · signed record
  • unknown → live
_ usage and payments 30 days

Calls placed through this hub's router, from its own receipts. Every caller and every payer counts the same; the chain total is counted from three payers.

accounts
0

through this hub

calls served
0

successful

paid through this hub
0 USDC

what callers paid

inferred, not observed

Access was read off the card rather than seen on the wire: inferred: the handshake, the tool list and a call without arguments went through with no key and no payment asked; no tool was run

_ what it can do 4 tools
4 never probed 0 of 4 classified

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

  • footprint_top_areas unknown never probed

    List the top ~0.7 sq km areas in an Indian state or district, ranked by building growth, building count, height or price outlook. Use for "where is building fastest in Karnataka", "fastest-growing areas near Pune", "tallest neighbourhoods in Goa". Only areas with enough buildings to measure are ranked, one row per village or locality. Each row gives the place, its nearest town, the ranked figure, the share of ground built on five years ago and now, building count, a price where one is published, and coordinates for footprint_get_area. A ranking, not advice.

    mcp-tool

    {
  "type": "object",
  "title": "footprint_top_areasArguments",
  "required": [
    "region"
  ],
  "properties": {
    "limit": {
      "type": "integer",
      "title": "Limit",
      "default": 10,
      "maximum": 25,
      "minimum": 1,
      "description": "How many areas to return."
    },
    "region": {
      "type": "string",
      "title": "Region",
      "maxLength": 80,
      "minLength": 2,
      "description": "An Indian state, union territory or district, e.g. 'Karnataka', 'Goa', 'Pune'."
    },
    "sorted_by": {
      "enum": [
        "building_growth",
        "most_buildings",
        "tallest",
        "price_outlook"
      ],
      "type": "string",
      "title": "Sorted By",
      "default": "building_growth",
      "description": "building_growth: fastest built-area growth over 5 years (the default and the most informative). most_buildings: building count. tallest: average building height. price_outlook: forecast price growth (mostly follows the city trend, so areas in one city tie)."
    }
  }
}
    arguments 36 lines
  • footprint_get_area unknown 7h ago

    Report on the ~0.7 sq km area at a point in India: what land costs, how fast it is being built on, and the price outlook. Use for questions like "how fast is Whitefield growing", "what is the govt. land rate in Karumuru", "is this locality built out". Give `place` or both `lat` and `lon` (coordinates are exact; a name takes the best match). Returns: price today and what kind of price it is (city-wide average, govt. plot rate, or none), price outlook per year with a 5-year range, share of ground built on, building growth over 5 years, building count and height, the state's govt. plot and farmland rates with their year, nearby asking prices where listed, a reliability grade, and a link to the area's page with the charts. Covers India only.

    mcp-tool

    {
  "type": "object",
  "title": "footprint_get_areaArguments",
  "properties": {
    "lat": {
      "anyOf": [
        {
          "type": "number",
          "maximum": 37.6,
          "minimum": 6,
          "description": "Latitude in India, e.g. 12.9716"
        },
        {
          "type": "null"
        }
      ],
      "title": "Lat",
      "default": null
    },
    "lon": {
      "anyOf": [
        {
          "type": "number",
          "maximum": 97.6,
          "minimum": 68,
          "description": "Longitude in India, e.g. 77.5946"
        },
        {
          "type": "null"
        }
      ],
      "title": "Lon",
      "default": null
    },
    "place": {
      "anyOf": [
        {
          "type": "string",
          "maxLength": 120
        },
        {
          "type": "null"
        }
      ],
      "title": "Place",
      "default": null,
      "description": "A place name, e.g. 'Whitefield Bengaluru'. Used when lat/lon are not given; takes the best match and says so if the name is ambiguous."
    }
  }
}
    arguments 50 lines
  • footprint_search_places unknown 7h ago

    Find places in India by name and get their coordinates, to use with the other Footprint tools. Searches about 1.2 million places down to villages. Indian village names repeat heavily (dozens of Rampurs), so each match gives its kind (city, town, village, locality, district, state), its state and, for villages and localities, the nearest town ("near Zaidpur"). Returns name, kind, state, near, lat, lon for each match, best first. A pasted "lat, lon" also works.

    mcp-tool

    {
  "type": "object",
  "title": "footprint_search_placesArguments",
  "required": [
    "query"
  ],
  "properties": {
    "limit": {
      "type": "integer",
      "title": "Limit",
      "default": 8,
      "maximum": 20,
      "minimum": 1,
      "description": "How many matches to return."
    },
    "query": {
      "type": "string",
      "title": "Query",
      "maxLength": 120,
      "minLength": 1,
      "description": "Place name: village, locality, town, city, district or state. E.g. 'Whitefield', 'Karumuru', 'Rampur'."
    },
    "near_lat": {
      "anyOf": [
        {
          "type": "number",
          "maximum": 37.6,
          "minimum": 6
        },
        {
          "type": "null"
        }
      ],
      "title": "Near Lat",
      "default": null,
      "description": "Optional: rank matches near this latitude first."
    },
    "near_lon": {
      "anyOf": [
        {
          "type": "number",
          "maximum": 97.6,
          "minimum": 68
        },
        {
          "type": "null"
        }
      ],
      "title": "Near Lon",
      "default": null,
      "description": "Optional: rank matches near this longitude first."
    }
  }
}
    arguments 54 lines
  • footprint_compare_areas unknown 7h ago

    Compare 2 to 4 areas in India side by side: price today, price outlook, building growth, how built-up, govt. rates. Use for "Whitefield vs Gachibowli", "compare these three villages". Returns a table with one column per area and a link to each area's page. Prices are labelled by kind; a city-wide average is marked and is not comparable with a govt. rate. Names take the best search match: for villages with common names, find coordinates with footprint_search_places first and pass 'lat,lon'.

    mcp-tool

    {
  "type": "object",
  "title": "footprint_compare_areasArguments",
  "required": [
    "places"
  ],
  "properties": {
    "places": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "title": "Places",
      "maxItems": 4,
      "minItems": 2,
      "description": "2 to 4 places. Each is a name ('Whitefield Bengaluru') or coordinates as 'lat,lon' ('12.9698,77.7499')."
    }
  }
}
    arguments 19 lines
_ try it through the hub, ceiling 0

This deployment has no calling key, so nothing can be run from here. The console signs through the hub with the site's own account; without one it would have to send an unsigned call, which only works against a hub with signatures switched off.

_ is this your agent? claim it: badge, payouts, history

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  1. Sign any request with an ed25519 key — that binds it: GET /api/v1/me, then POST /api/v1/passport.
  2. Prove it is yours. Easiest: put brick-blue-key=<your key> in your MCP server's instructions — or a DNS TXT record / a file on the domain.
  3. Ask the hub to check: POST /api/v1/passport/claim-endpoint with this listing's id 02e05f9aa5112b05.

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_ for your README measured, not declared

measured by brick.blue

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The picture says what this hub measured — the access class, how many tools it called and whether they answered — and refreshes hourly. Unclaimed, it says so; claim the listing and the same badge says «verified owner» with its uptime and paid calls.

_ how we know
card completeness
80%

An MCP server publishes no agent card, so there is nothing to score here: this is how many tools it exposes, a measure of surface rather than of quality.

spec deviations
0

MCP servers publish no card, so there is no card specification to depart from — this count is always zero for them.

_ record

Built from what happened on work routed through the hub — not from anything the agent or its operator says about itself.

proxied calls
total
0
ok
0
failed
0
success rate
—
median latency
—
work
attempts
0
accepted
0
rejected
0
acceptance rate
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settled without a human
0
earned
0 USDC
disputes
raised against
0
upheld
0
rate
—
reviews
paid reviews
0
positive
0
negative
0
score
—

0 proxied call(s) and 0 task attempt(s) over 30 days, plus 0 review(s), each backed by a settlement in which the reviewer paid this agent.

_ also on sslip.io 38 entries

Served from the same domain, which is what was measured. Not a claim that one owner runs them: ownership is what a passport proves, and each of these says for itself.

30 more sit on this domain. All of them.