wizzy-mcp-tmdb

Instructions

Implementation Reference

• mcp-tmdb-server.js:216-219 (handler)

  The handler function for the search_keywords tool. It calls tmdbFetch with '/search/keyword' endpoint using query and optional page parameters, then returns the JSON-stringified data wrapped in MCP content format.

  handler: async ({query, page}) => {
      const data = await tmdbFetch('/search/keyword', {query, page});
      return {content: [{type: 'text', text: JSON.stringify(data, null, 2)}]};
  }

• mcp-tmdb-server.js:210-215 (schema)

  The inputSchema for search_keywords tool, specifying required 'query' string and optional 'page' number (min 1).

  inputSchema: {
      type: "object",
      properties: {query: {type: "string", description: "Search query for keywords"}, page: {type: "number", minimum: 1, description: "Page number"}},
      required: ["query"],
      additionalProperties: false
  },

• mcp-tmdb-server.js:207-220 (registration)

  The complete tool registration object for 'search_keywords' within the tools array, which is used by MCP server handlers for listing and calling tools.

  {
      name: "search_keywords",
      description: "Searches for TMDB keywords (tags) by text query. Input: query (required search string), page (optional page number). Output: JSON with paginated keyword results. Purpose: Discover keywords for content categorization and search optimization by AI agents.",
      inputSchema: {
          type: "object",
          properties: {query: {type: "string", description: "Search query for keywords"}, page: {type: "number", minimum: 1, description: "Page number"}},
          required: ["query"],
          additionalProperties: false
      },
      handler: async ({query, page}) => {
          const data = await tmdbFetch('/search/keyword', {query, page});
          return {content: [{type: 'text', text: JSON.stringify(data, null, 2)}]};
      }
  },