get_ai_status

Instructions

Implementation Reference

• mcp-server/src/index.ts:96-116 (handler)

  The handler function for the 'get_ai_status' tool. It calls fetchJSON('/status') to get real-time operational status of major AI services (Claude, OpenAI, Gemini, Mistral, Cohere, Replicate, Hugging Face), formats the response, and returns the status text.

  server.tool(
    'get_ai_status',
    'Get real-time operational status of major AI services (Claude, OpenAI, Gemini, Mistral, Cohere, Replicate, Hugging Face).',
    {},
    async () => {
      const data = await fetchJSON('/status') as {
        services: { name: string; provider: string; status: string; components: { name: string; status: string }[] }[];
      };
  
      const text = data.services
        .map(s => {
          const components = s.components.length > 0
            ? '\n' + s.components.map(c => `     ${c.name}: ${c.status}`).join('\n')
            : '';
          return `  ${s.status === 'operational' ? 'OK' : s.status.toUpperCase()} ${s.name} (${s.provider})${components}`;
        })
        .join('\n');
  
      return { content: [{ type: 'text' as const, text: `AI Service Status:\n${text}` }] };
    }
  );

• mcp-server/src/index.ts:96-116 (registration)

  The tool is registered via server.tool() with the name 'get_ai_status', no input schema (empty object), and a description string.

  server.tool(
    'get_ai_status',
    'Get real-time operational status of major AI services (Claude, OpenAI, Gemini, Mistral, Cohere, Replicate, Hugging Face).',
    {},
    async () => {
      const data = await fetchJSON('/status') as {
        services: { name: string; provider: string; status: string; components: { name: string; status: string }[] }[];
      };
  
      const text = data.services
        .map(s => {
          const components = s.components.length > 0
            ? '\n' + s.components.map(c => `     ${c.name}: ${c.status}`).join('\n')
            : '';
          return `  ${s.status === 'operational' ? 'OK' : s.status.toUpperCase()} ${s.name} (${s.provider})${components}`;
        })
        .join('\n');
  
      return { content: [{ type: 'text' as const, text: `AI Service Status:\n${text}` }] };
    }
  );

• mcp-server/src/index.ts:99-99 (schema)

  Input schema for get_ai_status is an empty object (no parameters required). The response type is inferred from the async handler returning { content: [{ type: 'text', text: string }] }.

  {},

• mcp-server/src/index.ts:19-59 (helper)

  The fetchJSON helper function used by get_ai_status to make API calls to the TensorFeed API (API_BASE + '/status'). It handles headers, auth, and error responses.

  async function fetchJSON(path: string, opts: FetchOptions = {}): Promise<unknown> {
    const headers: Record<string, string> = {
      'User-Agent': `TensorFeed-MCP/${SDK_VERSION}`,
    };
    if (opts.body !== undefined) headers['Content-Type'] = 'application/json';
    if (opts.auth) {
      const token = process.env.TENSORFEED_TOKEN;
      if (!token) {
        throw new Error(
          'TENSORFEED_TOKEN env var is not set. Premium MCP tools require a bearer token. ' +
            'Buy credits at https://tensorfeed.ai/developers/agent-payments and pass the returned tf_live_... token via the TENSORFEED_TOKEN env var in your MCP client config.',
        );
      }
      headers['Authorization'] = `Bearer ${token}`;
    }
    const res = await fetch(`${API_BASE}${path}`, {
      method: opts.method ?? 'GET',
      headers,
      ...(opts.body !== undefined ? { body: JSON.stringify(opts.body) } : {}),
    });
    if (!res.ok) {
      let errPayload: unknown;
      try {
        errPayload = await res.json();
      } catch {
        errPayload = await res.text().catch(() => '');
      }
      if (res.status === 402) {
        throw new Error(
          `Payment required (402). Your token may be out of credits. Top up at https://tensorfeed.ai/developers/agent-payments. Detail: ${JSON.stringify(errPayload)}`,
        );
      }
      if (res.status === 401) {
        throw new Error(
          `Token rejected (401). Check that TENSORFEED_TOKEN is set to a valid tf_live_... token. Detail: ${JSON.stringify(errPayload)}`,
        );
      }
      throw new Error(`API error ${res.status}: ${JSON.stringify(errPayload)}`);
    }
    return res.json();
  }