Skip to main content
Glama
ClawyPro

Clawy MCP Server

by ClawyPro

tabelog_search

Search Japanese restaurants on Tabelog by area, cuisine, rating, or keyword to find dining options in Japan.

Instructions

Search Japanese restaurants on Tabelog — Japan's largest restaurant review site. Find by area, cuisine, rating, or keyword.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
areaNoArea name (e.g., 'Tokyo', 'Osaka', 'Shibuya', '渋谷')
cuisineNoCuisine type (e.g., 'sushi', 'ramen', 'izakaya', '寿司')
keywordNoFree text search keyword
min_ratingNoMinimum Tabelog rating (e.g., 3.5)
pageNoPage number (default 1)

Implementation Reference

  • The definition and schema for the tabelog_search tool.
    {
      name: "tabelog_search",
      description: "Search Japanese restaurants on Tabelog — Japan's largest restaurant review site. Find by area, cuisine, rating, or keyword.",
      inputSchema: z.object({
        area: z.string().optional().describe("Area name (e.g., 'Tokyo', 'Osaka', 'Shibuya', '渋谷')"),
        cuisine: z.string().optional().describe("Cuisine type (e.g., 'sushi', 'ramen', 'izakaya', '寿司')"),
        keyword: z.string().optional().describe("Free text search keyword"),
        min_rating: z.number().optional().describe("Minimum Tabelog rating (e.g., 3.5)"),
        page: z.number().optional().describe("Page number (default 1)"),
      }),
      endpoint: "/v1/tabelog/search",
    },
  • Generic tool handler that executes the tabelog_search logic by making an API request to the configured endpoint.
    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. It mentions the tool searches on Tabelog, but doesn't disclose behavioral traits such as rate limits, authentication needs, pagination details (beyond the 'page' parameter in schema), or what the output looks like (e.g., list of restaurants with details). This leaves significant gaps for an agent to understand how the tool behaves.

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 concise and well-structured in two sentences: the first states the purpose and context, and the second lists search criteria. Every sentence adds value without redundancy, making it easy to parse and front-loaded with key information.

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 (a search tool with 5 parameters), no annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects like rate limits or output format, and while the schema handles parameters well, the overall context for safe and effective use is lacking. This is inadequate for a tool with multiple inputs and no structured output information.

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?

The description adds minimal meaning beyond the input schema, which has 100% coverage with clear parameter descriptions. It lists search criteria ('area, cuisine, rating, or keyword'), aligning with schema parameters, but doesn't provide additional context like format examples or constraints (e.g., rating scale). With high schema coverage, the baseline is 3, and the description doesn't significantly enhance parameter understanding.

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: 'Search Japanese restaurants on Tabelog — Japan's largest restaurant review site.' It specifies the resource (Japanese restaurants) and the action (search), and provides context about Tabelog. However, it doesn't explicitly differentiate from sibling tools, which are unrelated search tools for different domains (e.g., financial, maps, academic).

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

Usage Guidelines3/5

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

The description implies usage context by listing search criteria ('Find by area, cuisine, rating, or keyword'), suggesting when to use this tool for restaurant searches. However, it lacks explicit guidance on when not to use it or alternatives (e.g., no mention of using other tools for non-restaurant searches). The sibling tools are for different purposes, so differentiation is implied but not stated.

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/ClawyPro/clawy-mcp-server'

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