Google Maps Menu Scraper

Google Maps

Operated by Sourcelane✓ verified

A Google Maps-focused menu scraper that extracts full restaurant menus as structured, spreadsheet-ready rows: one row per menu item including its menu section, dish name, description, displayed price and a parsed numeric price with currency, item position and total items, plus per-row restaurant metadata (name, address, category, rating, review count, price level, official menu link when available), unique place identifiers and search provenance, and a scrape timestamp. Operates by scraping Google Maps place records and parsing structured menu data; supports searching by cuisine+city or by supplying place URLs/IDs and bulk processing across queries and place lists. Technical features include session rotation, proxy escalation and retry logic to re-request incomplete place records, parsing and normalizing price values and currencies, and optional inclusion of restaurants that lack a structured menu by returning a single record with the restaurant’s external menu link.

Verified Sep 28, 3:55 AM

$0.0005

per menu item

Up to 100 per call. Only pay for results returned; failed calls are refunded.

What people use it for

Menu price intelligence: compare dish prices across a city, cuisine, or competitor set and track price changes over time
Food delivery and aggregator catalog seeding: collect menus and prices for large restaurant sets
Market research: analyze which dishes, ingredients, or price points dominate a neighborhood
Restaurant sales prospecting: identify restaurants with sparse or missing structured menus for outreach
Nutrition and recipe results: compile dish names and descriptions at scale

Trust & reliability

7d uptime trend

Window	Uptime	Success rate	p50	p95
24h	—	—	—	—
7d	—	—	—	—
30d	—	—	—	—

Calling contract

Call it through Sourcelane's gateway or MCP server. We run the connector, apply your agent's spend guardrails, and bill only the results returned.

Call it via Sourcelane

curl -X POST https://api.usesourcelane.com/v1/call \
  -H "Authorization: Bearer sl_live_your_agent_key" \
  -H "Content-Type: application/json" \
  -d '{"listing":"google-maps-menu-scraper","params":{"searchQueries":["pizza restaurants in Chicago"],"maxPlacesPerQuery":5},"maxResults":10}'

Request params

Field	Type	Required	Description
`searchQueries`	array	optional	Restaurants to search on Google Maps, one query per line — e.g. "pizza restaurants in Chicago", "sushi in Soho London".
`placeUrls`	array	optional	Alternatively (or additionally) scrape menus for specific restaurants — Google Maps place URLs, maps.app.goo.gl short links, ?cid= links, Place IDs (ChIJ…) or hex IDs (0x…:0x…).
`maxPlacesPerQuery`	integer	optional	Maximum number of restaurants to process per search query (Google Maps returns at most ~120 per query). 0 = everything Google returns. Capped at 100 per call.
`includePlacesWithoutMenu`	boolean	optional	Restaurants with no structured menu on Google Maps are skipped by default. Enable to save one row per such restaurant anyway (with its menuUrl link, if any).
`language`	string	optional	Language code for results, e.g. en, de, fr, es, pt-BR.
`country`	string	optional	Two-letter country code that biases search results, e.g. us, gb, de, au.

Each result contains

Field	Type	Description
`placeId`	string	Place Id
`googlePlaceId`	string	Google Place Id
`placeName`	string	Place Name
`placeAddress`	string	Place Address
`placeCategory`	string	Place Category
`placeRating`	number	Place Rating
`placeReviewCount`	integer	Place Review Count
`placePriceLevel`	string	Place Price Level
`placeUrl`	string	Place Url
`menuUrl`	string	Menu Url
`searchQuery`	string	Search Query
`section`	string	Section
`itemName`	string	—
`itemDescription`	string	—
`price`	string	—
`priceValue`	integer	—
`currency`	string	—
`itemIndex`	integer	—
`totalItems`	integer	—
`scrapedAt`	string	—

Use Google Maps Menu Scraper from Claude, ChatGPT or Cursor

Pick your tool and connect in under a minute. Then just ask — for example: “List 40 dentists in Austin TX with phone, website and rating above 4.5.”

Connect Claude

Web, desktop and mobile. Paste one URL.

1Copy your personal connector URL
2In Claude open Settings → Connectors → Add custom connector
3Paste the URL and click Add — done

Manual setup (config files, REST, Python) +

Claude Code

Adds the Sourcelane MCP server with your key as a header.

terminal

claude mcp add --transport http sourcelane https://api.usesourcelane.com/mcp \
  --header "Authorization: Bearer sl_live_your_agent_key"

Claude Desktop (config file)

Alternative to the connector URL: add to claude_desktop_config.json, then restart Claude.

claude_desktop_config.json

{
  "mcpServers": {
    "sourcelane": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://api.usesourcelane.com/mcp",
        "--header",
        "Authorization:${AUTH_HEADER}"
      ],
      "env": {
        "AUTH_HEADER": "Bearer sl_live_your_agent_key"
      }
    }
  }
}

Cursor & Windsurf

Add to ~/.cursor/mcp.json (or Windsurf's mcp_config.json).

mcp.json

{
  "mcpServers": {
    "sourcelane": {
      "url": "https://api.usesourcelane.com/mcp",
      "headers": {
        "Authorization": "Bearer sl_live_your_agent_key"
      }
    }
  }
}

VS Code

Save as .vscode/mcp.json. VS Code prompts for your key once.

.vscode/mcp.json

{
  "servers": {
    "sourcelane": {
      "type": "http",
      "url": "https://api.usesourcelane.com/mcp",
      "headers": {
        "Authorization": "Bearer ${input:sourcelane-key}"
      }
    }
  },
  "inputs": [
    {
      "type": "promptString",
      "id": "sourcelane-key",
      "description": "Sourcelane agent key",
      "password": true
    }
  ]
}

ChatGPT Custom GPT (Actions)

Create a GPT → Actions → Import from URL, then Authentication: API Key, Bearer.

OpenAPI schema URL

https://usesourcelane.com/openapi.json

REST

One POST. Pass maxResults to cap cost.

curl

curl -X POST https://api.usesourcelane.com/v1/call \
  -H "Authorization: Bearer sl_live_your_agent_key" \
  -H "Content-Type: application/json" \
  -d '{"listing":"google-maps-menu-scraper","params":{"searchQueries":["pizza restaurants in Chicago"],"maxPlacesPerQuery":5},"maxResults":10}'

Python, LangChain, CrewAI, OpenAI Agents SDK…

Wrap the REST call as a tool, or point an MCP client at the endpoint.

python

import requests

res = requests.post(
    "https://api.usesourcelane.com/v1/call",
    headers={"Authorization": "Bearer sl_live_your_agent_key"},
    json={
        "listing": "google-maps-menu-scraper",
        "params": {"searchQueries":["pizza restaurants in Chicago"],"maxPlacesPerQuery":5},
        "maxResults": 10,
    },
    timeout=300,
)
body = res.json()
print(body["receipt"]["chargedMicros"], "micro-USD for", body["receipt"]["results"], "results")
print(body["data"])

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