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ClawyPro

Clawy MCP Server

by ClawyPro

google_maps_directions

Get directions between two locations using Google Maps. Supports driving, walking, bicycling, and transit modes for route planning.

Instructions

Get directions between two points via Google Maps. Supports driving, walking, bicycling, and transit modes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
originYesStarting point (address or lat,lng)
destinationYesDestination (address or lat,lng)
modeNoTravel mode (default: driving)
languageNoLanguage for instructions

Implementation Reference

  • The tool definition for `google_maps_directions`, specifying its input schema and API endpoint.
      name: "google_maps_directions",
      description: "Get directions between two points via Google Maps. Supports driving, walking, bicycling, and transit modes.",
      inputSchema: z.object({
        origin: z.string().describe("Starting point (address or lat,lng)"),
        destination: z.string().describe("Destination (address or lat,lng)"),
        mode: z.enum(["driving", "walking", "bicycling", "transit"]).optional()
          .describe("Travel mode (default: driving)"),
        language: z.string().optional().describe("Language for instructions"),
      }),
      endpoint: "/v1/google-maps/directions",
    },
  • The generic handler registration that maps all tools (including `google_maps_directions`) to a gateway request.
    for (const tool of allTools) {
      server.tool(
        tool.name,
        tool.description,
        tool.inputSchema.shape,
        async (params) => {
          const method = tool.method || "POST";
          const result = await gatewayRequest(method, tool.endpoint, params as Record<string, unknown>);
    
          if (result.error) {
            return {
              content: [{ type: "text" as const, text: `Error (${result.status}): ${result.error}` }],
              isError: true,
            };
          }
    
          const text = typeof result.data === "string"
            ? result.data
            : JSON.stringify(result.data, null, 2);
    
          return {
            content: [{ type: "text" as const, text }],
          };
        },
      );
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool 'Supports driving, walking, bicycling, and transit modes,' which adds some context about capabilities. However, it lacks critical details such as rate limits, authentication requirements, error handling, or what the output looks like (e.g., route steps, duration). For a tool with no annotations, this is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise and front-loaded: two sentences that directly state the tool's purpose and key features without any fluff. Every word earns its place, making it easy for an AI agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of a directions tool (involving multiple parameters, modes, and no output schema), the description is incomplete. It lacks details on output format, error cases, or behavioral traits like rate limits. With no annotations and no output schema, the description should provide more context to help an AI agent use the tool effectively, but it falls short.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, meaning the input schema already documents all parameters thoroughly (e.g., 'origin' as 'Starting point (address or lat,lng)'). The description adds minimal value by implying parameter usage through 'between two points' and listing travel modes, but doesn't provide additional semantics beyond what the schema offers. This meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get directions between two points via Google Maps.' It specifies the verb ('Get directions') and resource ('between two points via Google Maps'), and mentions supported travel modes. However, it doesn't explicitly differentiate from sibling tools like 'google_maps_geocode' or 'google_maps_places', which prevents a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools (e.g., 'google_maps_geocode' for address lookup or 'tmap_route' for alternative routing), prerequisites, or specific contexts where this tool is preferred. The lack of comparative or contextual advice limits its utility for an AI agent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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