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garylab
by garylab

google_search_places

Search Google for locations, businesses, or points of interest. Specify queries, countries, languages, and pages to retrieve relevant, up-to-date data via the Serper MCP Server.

Instructions

Search Google for results

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
autocorrectNoAutomatically correct
glNoThe country to search in, e.g. us, uk, ca, au, etc.
hlNoThe language to search in, e.g. en, es, fr, de, etc.
locationNoThe location to search in, e.g. San Francisco, CA, USA
pageNoThe page number to return, first page is 1
qYesThe query to search for

Implementation Reference

  • Core handler function that constructs the Serper API URL for 'google_search_places' (uri_path='places') and calls fetch_json to execute the HTTP POST request.
    async def google(tool: SerperTools, request: BaseModel) -> Dict[str, Any]: uri_path = tool.value.split("_")[-1] url = f"https://google.serper.dev/{uri_path}" return await fetch_json(url, request)
  • Helper function that performs the actual HTTP POST to the Serper API endpoint with the request payload.
    async def fetch_json(url: str, request: BaseModel) -> Dict[str, Any]: payload = request.model_dump(exclude_none=True) headers = { 'X-API-KEY': SERPER_API_KEY, 'Content-Type': 'application/json' } ssl_context = ssl.create_default_context(cafile=certifi.where()) connector = aiohttp.TCPConnector(ssl=ssl_context) timeout = aiohttp.ClientTimeout(total=AIOHTTP_TIMEOUT) async with aiohttp.ClientSession(connector=connector, timeout=timeout) as session: async with session.post(url, headers=headers, json=payload) as response: response.raise_for_status() return await response.json()
  • MCP server tool registration via @server.list_tools(), iterates over google_request_map (which includes 'google_search_places') to register tools with their schemas.
    @server.list_tools() async def list_tools() -> List[Tool]: tools = [] for k, v in google_request_map.items(): tools.append( Tool( name=k.value, description="Search Google for results", inputSchema=v.model_json_schema(), ), ) tools.append(Tool( name=SerperTools.WEBPAGE_SCRAPE, description="Scrape webpage by url", inputSchema=WebpageRequest.model_json_schema(), )) return tools
  • Mapping of tool names (SerperTools.GOOGLE_SEARCH_PLACES = 'google_search_places') to their input schema classes, used in list_tools and call_tool.
    google_request_map = { SerperTools.GOOGLE_SEARCH: SearchRequest, SerperTools.GOOGLE_SEARCH_IMAGES: SearchRequest, SerperTools.GOOGLE_SEARCH_VIDEOS: SearchRequest, SerperTools.GOOGLE_SEARCH_PLACES: AutocorrectRequest, SerperTools.GOOGLE_SEARCH_MAPS: MapsRequest, SerperTools.GOOGLE_SEARCH_REVIEWS: ReviewsRequest, SerperTools.GOOGLE_SEARCH_NEWS: SearchRequest, SerperTools.GOOGLE_SEARCH_SHOPPING: ShoppingRequest, SerperTools.GOOGLE_SEARCH_LENS: LensRequest, SerperTools.GOOGLE_SEARCH_SCHOLAR: AutocorrectRequest, SerperTools.GOOGLE_SEARCH_PATENTS: PatentsRequest, SerperTools.GOOGLE_SEARCH_AUTOCOMPLETE: AutocorrectRequest, }
  • Input schema for 'google_search_places' tool (AutocorrectRequest, inherits from BaseRequest with query params). Used to validate arguments and generate inputSchema.
    class AutocorrectRequest(BaseRequest): autocorrect: Optional[str] = Field( "true", pattern=r"^(true|false)$", description="Automatically correct (boolean value as string: 'true' or 'false')", )
  • MCP @server.call_tool() handler that dispatches 'google_search_places' calls: validates tool name, instantiates schema, calls core google() function, and returns JSON result.
    @server.call_tool() async def call_tool(name: str, arguments: dict[str, Any]) -> Sequence[TextContent | ImageContent | EmbeddedResource]: if not SERPER_API_KEY: return [TextContent(text=f"SERPER_API_KEY is empty!", type="text")] try: if name == SerperTools.WEBPAGE_SCRAPE.value: request = WebpageRequest(**arguments) result = await scape(request) return [TextContent(text=json.dumps(result, indent=2), type="text")] if not SerperTools.has_value(name): raise ValueError(f"Tool {name} not found") tool = SerperTools(name) request = google_request_map[tool](**arguments) result = await google(tool, request) return [TextContent(text=json.dumps(result, indent=2), type="text")] except Exception as e: return [TextContent(text=f"Error: {str(e)}", type="text")]

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