list_watches

Instructions

Implementation Reference

• mcp-server/src/index.ts:775-806 (handler)

  The list_watches tool handler: fetches watches from /premium/watches endpoint, formats them into a readable text output, or returns 'No active watches.' if count is 0.

  server.tool(
    'list_watches',
    'List the active webhook watches owned by the configured TensorFeed token. Free, requires TENSORFEED_TOKEN.',
    {},
    async () => {
      const data = (await fetchJSON('/premium/watches', { auth: true })) as {
        count: number;
        watches: {
          id: string;
          spec: { type: string; model?: string; field?: string; op?: string; threshold?: number; provider?: string; value?: string };
          callback_url: string;
          fire_count: number;
          fire_cap: number;
          expires_at: string;
          status: string;
        }[];
      };
      if (data.count === 0) {
        return { content: [{ type: 'text' as const, text: 'No active watches.' }] };
      }
      const rows = data.watches
        .map(w => {
          const desc =
            w.spec.type === 'price'
              ? `${w.spec.model} ${w.spec.field} ${w.spec.op}${w.spec.threshold !== undefined ? ' ' + w.spec.threshold : ''}`
              : `${w.spec.provider} ${w.spec.op}${w.spec.value ? ' ' + w.spec.value : ''}`;
          return `  ${w.id} (${w.status}) [${w.spec.type}] ${desc}\n     -> ${w.callback_url}\n     fired ${w.fire_count}/${w.fire_cap}, expires ${w.expires_at}`;
        })
        .join('\n\n');
      return { content: [{ type: 'text' as const, text: `${data.count} active watches:\n\n${rows}` }] };
    },
  );

• mcp-server/src/index.ts:775-806 (registration)

  The tool is registered via server.tool('list_watches', ...) on the McpServer instance. Registration includes the tool name, description, empty schema (no parameters), and the handler function.

  server.tool(
    'list_watches',
    'List the active webhook watches owned by the configured TensorFeed token. Free, requires TENSORFEED_TOKEN.',
    {},
    async () => {
      const data = (await fetchJSON('/premium/watches', { auth: true })) as {
        count: number;
        watches: {
          id: string;
          spec: { type: string; model?: string; field?: string; op?: string; threshold?: number; provider?: string; value?: string };
          callback_url: string;
          fire_count: number;
          fire_cap: number;
          expires_at: string;
          status: string;
        }[];
      };
      if (data.count === 0) {
        return { content: [{ type: 'text' as const, text: 'No active watches.' }] };
      }
      const rows = data.watches
        .map(w => {
          const desc =
            w.spec.type === 'price'
              ? `${w.spec.model} ${w.spec.field} ${w.spec.op}${w.spec.threshold !== undefined ? ' ' + w.spec.threshold : ''}`
              : `${w.spec.provider} ${w.spec.op}${w.spec.value ? ' ' + w.spec.value : ''}`;
          return `  ${w.id} (${w.status}) [${w.spec.type}] ${desc}\n     -> ${w.callback_url}\n     fired ${w.fire_count}/${w.fire_cap}, expires ${w.expires_at}`;
        })
        .join('\n\n');
      return { content: [{ type: 'text' as const, text: `${data.count} active watches:\n\n${rows}` }] };
    },
  );

• mcp-server/src/index.ts:778-778 (schema)

  The schema for list_watches is an empty object {}, meaning the tool takes no input parameters.

  {},

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

  The fetchJSON helper function is used by the list_watches handler to make authenticated API calls to the TensorFeed API.

  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();
  }