is_service_down

Instructions

Implementation Reference

• mcp-server/src/index.ts:120-152 (handler)

  The tool handler for 'is_service_down'. It fetches service status from the TensorFeed API, finds a matching service by name/provider, and returns its operational status.

  server.tool(
    'is_service_down',
    'Check if a specific AI service is currently down or experiencing issues.',
    {
      service: z.string().describe('Service name to check (e.g. "claude", "openai", "gemini", "mistral", "cohere", "hugging face", "replicate")'),
    },
    async ({ service }) => {
      const data = await fetchJSON('/status') as {
        services: { name: string; provider: string; status: string; components: { name: string; status: string }[] }[];
      };
  
      const match = data.services.find(s =>
        s.name.toLowerCase().includes(service.toLowerCase()) ||
        s.provider.toLowerCase().includes(service.toLowerCase())
      );
  
      if (!match) {
        return { content: [{ type: 'text' as const, text: `Service "${service}" not found. Available services: ${data.services.map(s => s.name).join(', ')}` }] };
      }
  
      const statusEmoji = match.status === 'operational' ? 'OK' : match.status === 'degraded' ? 'DEGRADED' : 'DOWN';
      const components = match.components.length > 0
        ? '\nComponents:\n' + match.components.map(c => `  ${c.name}: ${c.status}`).join('\n')
        : '';
  
      return {
        content: [{
          type: 'text' as const,
          text: `${statusEmoji} ${match.name} (${match.provider}) is ${match.status}${components}`
        }]
      };
    }
  );

• mcp-server/src/index.ts:123-125 (schema)

  The input schema for the 'is_service_down' tool, accepting a 'service' string parameter.

  {
    service: z.string().describe('Service name to check (e.g. "claude", "openai", "gemini", "mistral", "cohere", "hugging face", "replicate")'),
  },

• mcp-server/src/index.ts:120-152 (registration)

  Registration of the 'is_service_down' tool via the McpServer.tool() method.

  server.tool(
    'is_service_down',
    'Check if a specific AI service is currently down or experiencing issues.',
    {
      service: z.string().describe('Service name to check (e.g. "claude", "openai", "gemini", "mistral", "cohere", "hugging face", "replicate")'),
    },
    async ({ service }) => {
      const data = await fetchJSON('/status') as {
        services: { name: string; provider: string; status: string; components: { name: string; status: string }[] }[];
      };
  
      const match = data.services.find(s =>
        s.name.toLowerCase().includes(service.toLowerCase()) ||
        s.provider.toLowerCase().includes(service.toLowerCase())
      );
  
      if (!match) {
        return { content: [{ type: 'text' as const, text: `Service "${service}" not found. Available services: ${data.services.map(s => s.name).join(', ')}` }] };
      }
  
      const statusEmoji = match.status === 'operational' ? 'OK' : match.status === 'degraded' ? 'DEGRADED' : 'DOWN';
      const components = match.components.length > 0
        ? '\nComponents:\n' + match.components.map(c => `  ${c.name}: ${c.status}`).join('\n')
        : '';
  
      return {
        content: [{
          type: 'text' as const,
          text: `${statusEmoji} ${match.name} (${match.provider}) is ${match.status}${components}`
        }]
      };
    }
  );

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

  The fetchJSON helper used by the tool to call the TensorFeed API endpoint.

  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();
  }