Skip to main content
Glama

search_dining

Read-onlyIdempotent

Find restaurants and check reservation availability by searching with filters like city, date, time, cuisine, party size, neighborhood, and price range.

Instructions

Search restaurants, dining options, and reservation availability by city, date, time, cuisine, party size, neighborhood, and price range. Use this when the user wants to find a restaurant, book dinner, plan a meal, get reservations, or pick a place to eat on a trip. Dining partnerships are in progress; surfaces availability today, full reservation flow in the next release.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYesCity name (e.g., 'Miami', 'New York', 'Key West')
dateYesReservation date (YYYY-MM-DD)
timeNoPreferred time in 24h format (e.g., '19:00' for 7pm)
party_sizeNoNumber of guests (1-20, default: 2)
cuisineNoCuisine filter (e.g., 'Italian', 'Seafood', 'Japanese')
price_rangeNoPrice range filter
neighborhoodNoNeighborhood filter (e.g., 'South Beach', 'Midtown')

Implementation Reference

  • The 'search_dining' tool definition and input schema — describes the tool as searching restaurants/dining options by city, date, time, party size, cuisine, price range, and neighborhood. Requires 'city' and 'date'.
    {
      name: "search_dining",
      description:
        "Search restaurants, dining options, and reservation availability by city, date, time, cuisine, party size, neighborhood, and price range. Use this when the user wants to find a restaurant, book dinner, plan a meal, get reservations, or pick a place to eat on a trip. Dining partnerships are in progress; surfaces availability today, full reservation flow in the next release.",
      inputSchema: {
        type: "object" as const,
        properties: {
          city: { type: "string", description: "City name (e.g., 'Miami', 'New York', 'Key West')" },
          date: { type: "string", description: "Reservation date (YYYY-MM-DD)" },
          time: { type: "string", description: "Preferred time in 24h format (e.g., '19:00' for 7pm)" },
          party_size: { type: "number", description: "Number of guests (1-20, default: 2)" },
          cuisine: { type: "string", description: "Cuisine filter (e.g., 'Italian', 'Seafood', 'Japanese')" },
          price_range: {
            type: "string",
            enum: ["$", "$$", "$$$", "$$$$"],
            description: "Price range filter",
          },
          neighborhood: { type: "string", description: "Neighborhood filter (e.g., 'South Beach', 'Midtown')" },
        },
        required: ["city", "date"],
      },
    },
  • The handler for 'search_dining' — calls apiCall('POST', '/v1/dining/search', args) to the backend API and returns the raw JSON result with no trimming.
    case "search_dining": {
      const result = await apiCall("POST", "/v1/dining/search", args);
      return { content: [{ type: "text", text: JSON.stringify(result, null, 2) }] };
    }
  • src/server.ts:508-508 (registration)
    Annotation registration for 'search_dining' in TOOL_ANNOTATIONS, marking it as readOnlyHint: true, idempotentHint: true, openWorldHint: true with title 'Search Restaurants & Dining'.
    search_dining: { title: "Search Restaurants & Dining", readOnlyHint: true, destructiveHint: false, idempotentHint: true, openWorldHint: true },
  • The apiCall helper used by the search_dining handler to make POST requests to the Autonomad API.
    async function apiCall(
      method: string,
      path: string,
      body?: Record<string, unknown>
    ): Promise<unknown> {
      const url = `${API_BASE}${path}`;
      const headers: Record<string, string> = { "Content-Type": "application/json" };
      const key = await ensureMcpKey();
      if (key) headers["x-mcp-key"] = key;
      const options: RequestInit = { method, headers };
      if (body) {
        options.body = JSON.stringify(body);
      }
      const res = await fetch(url, options);
      if (!res.ok) {
        const error = await res.text();
        throw new Error(`API error ${res.status}: ${error}`);
      }
      return res.json();
    }
Behavior5/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description reinforces this by stating 'search' and 'reservation availability', implying no mutation. It adds context about partnership status and release timeline, which helps set expectations. No contradiction with annotations.

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 three sentences: first defines the action and filters, second states use cases, third provides status. It is front-loaded with key information, no unnecessary words, and easy to parse.

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?

The description covers purpose, usage guidelines, and behavioral context well. However, it does not describe the return format (e.g., list of restaurants with availability details), which would be helpful since there is no output schema. Minor gap given the tool's complexity.

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 descriptions for all 7 parameters. The description lists the parameters in a sentence but does not add new semantics or usage tips beyond the schema. It provides a natural language summary but does not enhance understanding of parameter relationships or defaults.

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 the tool searches for restaurants and dining options with reservation availability, specifying multiple filtering dimensions (city, date, time, cuisine, etc.). This distinguishes it from sibling search tools like search_hotels or search_events, which target different domains.

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

Usage Guidelines5/5

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

Explicitly states when to use: 'when the user wants to find a restaurant, book dinner, plan a meal, get reservations, or pick a place to eat on a trip.' Also provides context on current limitations ('surfaces availability today') and future plans ('full reservation flow in the next release'), guiding the agent on expected behavior.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Autonomad1/autonomad-travel'

If you have feedback or need assistance with the MCP directory API, please join our Discord server