HubVibe Maps Places Search

x402

HubVibe Maps Places Search is a paid API for AI agents from hubvibe-io.com, paid per call via x402, $0.1/call, status unknown (last checked 2026-10-11).

Search for businesses, addresses, and points of interest using Google Maps Grounding via a paid API endpoint

Price / call$0.1

Seller volume →—

Success—

StatusUnknown

How this service works

Places near me / local search anywhere: 'coffee near the Ferry Building, San Francisco', 'ramen near Shibuya Station', 'pharmacy' at coordinates. From Overture Maps open places data (80M+ places): name, category, distance, address, website, phone, brand, open status and confidence, nearest first; the area widens when nothing is close. Input: query; optional near, lat and lng, radius_m, limit.

Output

A list of matching places including business names, addresses, and relevant location details sourced from Google Maps, filtered to the query and optional region bias.

Example use cases

Finding restaurants near a venue

“Can you find Italian restaurants near Madison Square Garden in New York? I'm going to a game tonight and want options within walking distance.”

Locating pharmacies in a city

“Search for 24-hour pharmacies in downtown Chicago — I need one that's open late tonight.”

Discovering coworking spaces abroad

“Find coworking spaces or business centers in Lisbon, Portugal — I'll be working remotely there next month.”

Technical details

Endpoint

POSThttps://hubvibe-io.com/work/maps/places?utm_source=zero.xyz

When to prefer

Choose this endpoint when you need Google Maps-quality place search results grounded in real business data, especially for local business discovery, address lookup, or POI search. It is preferable to generic web search when structured place data (names, addresses, categories) is needed rather than editorial content about a location.

Side effects

Maps Grounding Lite API key not configured by operator — endpoint returns unavailable error
Vague or ambiguous query returns irrelevant results
Region code not recognized or malformed — may fall back to global results
No matching places found for the query in the specified region
Rate limiting or payment failure on the $0.10 USDC per-call charge

Input

Schema · Request body

Field	Type	Description
lat	number
lng	number
near	string
limit	integer
query	string
language	string
radius_m	number
region_code	string

Output

Schema · Response

{
  "type": "json",
  "example": {
    "result": {
      "near": {
        "lat": 37.7955,
        "lon": -122.3937,
        "name": "San Francisco Ferry Building (building in San Francisco)",
        "source": "Wikidata Q1060289"
      },
      "what": "coffee",
      "notes": [],
      "query": "coffee near the Ferry Building, San Francisco",
      "places": [
        {
          "id": "8333e7a5-b1ca-4c61-969d-5543d8de977a",
          "lat": 37.7953,
          "lon": -122.3931,
          "name": "Red Bay Coffee Ferry Building",
          "brand": "Red Bay Coffee",
          "phone": "(415) 983-8000",
          "address": "Ferry Building, 1, San Francisco, CA, 94111",
          "country": "US",
          "sources": [
            "meta"
          ],
          "website": "http://redbaycoffee.com",
          "category": "coffee_shop",
          "confidence": 0.942,
          "distance_m": 54,
          "operating_status": "open"
        }
      ],
      "radius_m": 1000,
      "checked_at": "2026-09-26T18:00:00Z",
      "attribution": [
        {
          "url": "https://docs.overturemaps.org/attribution/",
          "text": "Places data from Overture Maps Foundation ..."
        }
      ],
      "place_count": 10
    },
    "status": "ok",
    "worker": "maps.places",
    "price_usd": 0.1,
    "provenance": {
      "steps": [
        {
          "ms": 640,
          "ok": true,
          "step": "places",
          "provider": "places"
        }
      ],
      "attempts": 1,
      "elapsed_ms": 660,
      "providers_used": [
        "places"
      ]
    },
    "receipt_id": "rcpt_9f1c2b3a4d5e6f70",
    "receipt_url": "/work/receipts/rcpt_9f1c2b3a4d5e6f70"
  }
}

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