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qa

Read-only

Retrieve questions and answers from a Google Business Profile, including authors, dates, and upvotes. Each request costs 1 credit.

Instructions

Get Questions & Answers from a Google Business Profile. Returns questions with their answers, authors, dates, and upvotes. Costs 1 credit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
business_nameYesBusiness name
locationYesCity and state
place_idNoGoogle Place ID for exact match

Implementation Reference

  • src/server.ts:36-36 (registration)
    The 'qa' tool is registered via registerBusinessTools(server, getAuth) call, which is imported from src/tools/business.ts
    registerBusinessTools(server, getAuth);
  • The 'qa' tool handler function. Defines the tool with name 'qa', description, input schema (business_name, location, place_id), and the async handler that calls the API at /v1/business/qa.
    server.tool(
      "qa",
      "Get Questions & Answers from a Google Business Profile. Returns questions with their answers, authors, dates, and upvotes. Costs 1 credit.",
      {
        business_name: z.string().describe("Business name"),
        location: z.string().describe("City and state"),
        place_id: z.string().optional().describe("Google Place ID for exact match"),
      },
      READ_ONLY,
      withErrorHandling(async ({ business_name, location, place_id }) => {
        const result = await callApi(
          "/v1/business/qa",
          { business_name, location, ...(place_id && { place_id }) },
          getAuth()
        );
        return { content: [{ type: "text" as const, text: formatResult(result.data, result) }] };
      })
    );
  • Input schema for the 'qa' tool using Zod: business_name (string), location (string), and optional place_id (string).
    {
      business_name: z.string().describe("Business name"),
      location: z.string().describe("City and state"),
      place_id: z.string().optional().describe("Google Place ID for exact match"),
    },
  • The callApi helper function used by the 'qa' tool handler to make POST requests to the API endpoint.
    export async function callApi(
      path: string,
      body: Record<string, unknown>,
      authHeader: string,
      timeoutMs = 60_000
    ): Promise<{ data: unknown; credits_used: number; credits_remaining: number; cached: boolean }> {
      const url = `${env.API_BASE_URL}${path}`;
    
      console.log(`[api] POST ${url} (timeout: ${timeoutMs / 1000}s, auth: ${authHeader ? `${authHeader.slice(0, 15)}...` : "MISSING"})`);
    
      const response = await fetch(url, {
        method: "POST",
        headers: {
          "Content-Type": "application/json",
          Authorization: authHeader,
        },
        body: JSON.stringify(body),
        signal: AbortSignal.timeout(timeoutMs),
      });
    
      if (!response.ok) {
        const text = await response.text();
        console.error(`[api] ${response.status} ${response.statusText} from ${path}: ${text.slice(0, 200)}`);
        // Try to parse as structured error
        try {
          const result = JSON.parse(text) as ApiErrorResponse;
          if (result.status === "error") {
            const err = result.error;
            const reqId = result.request_id ? ` [request_id: ${result.request_id}]` : "";
            throw new Error(
              err.required_credits
                ? `${err.message} (requires ${err.required_credits} credits, balance: ${err.current_balance})${reqId}`
                : `${err.message}${reqId}`
            );
          }
        } catch (parseErr) {
          if (parseErr instanceof Error && parseErr.message !== "error") {
            // Re-throw if it's our structured error from above
            if (!text.includes('"status":"error"')) {
              throw new Error(`API returned ${response.status}: ${text.slice(0, 200)}`);
            }
            throw parseErr;
          }
        }
        throw new Error(`API returned ${response.status}: ${text.slice(0, 200)}`);
      }
    
      const result = (await response.json()) as ApiResponse;
    
      if (result.status === "error") {
        const err = (result as ApiErrorResponse).error;
        const reqId = (result as ApiErrorResponse).request_id ? ` [request_id: ${(result as ApiErrorResponse).request_id}]` : "";
        throw new Error(
          err.required_credits
            ? `${err.message} (requires ${err.required_credits} credits, balance: ${err.current_balance})${reqId}`
            : `${err.message}${reqId}`
        );
      }
    
      console.log(`[api] ${path} OK (${result.credits_used} credits used, ${result.credits_remaining} remaining)`);
    
      return {
        data: result.data,
        credits_used: result.credits_used,
        credits_remaining: result.credits_remaining,
        cached: result.cached,
      };
    }
  • The withErrorHandling wrapper that provides error handling for the 'qa' tool handler.
    export function withErrorHandling<T>(
      fn: (args: T) => Promise<ToolResult>
    ): (args: T) => Promise<ToolResult> {
      return async (args) => {
        try {
          return await fn(args);
        } catch (err) {
          const message = err instanceof Error ? err.message : String(err);
          console.error(`[mcp] Tool error: ${message}`);
          return {
            content: [{ type: "text" as const, text: `Error: ${message}` }],
            isError: true,
          };
        }
      };
    }
Behavior4/5

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

Annotations already confirm read-only and non-destructive behavior. Description adds value by stating the exact credit cost (1 credit), which is beyond annotation scope. No hidden side effects mentioned.

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?

Two sentences, front-loaded with purpose and return details, no fluff. Second sentence adds a critical constraint (cost) without redundancy.

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

Completeness4/5

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

For a simple read-only tool with no output schema, description adequately covers input, output fields, and cost. Could mention pagination or limits, but not essential for basic use.

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 coverage is 100% with basic descriptions. Tool description does not enrich parameter meaning (e.g., how 'place_id' interacts with name/location). Baseline 3 applies since schema already covers parameters.

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

Purpose5/5

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

The description clearly states it retrieves Q&A from a Google Business Profile with specific return fields (questions, answers, authors, dates, upvotes), distinguishing it from sibling tools like 'business_profile' and 'google_reviews'.

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?

No guidance on when to use this tool versus alternatives (e.g., 'business_profile' for general profile info, 'google_reviews' for reviews). Context signals show many related tools, but description lacks comparative cues.

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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