Unit 9 · Connect to external tools and data

Handle long-running MCP work

You can monitor progress, provide requested input, cancel, or resume work that finishes later. Recording and deterministic replay make the protocol lifecycle testable.

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Worked example

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const task = await client.callTool({ name, arguments: input, task: { ttl: 60_000 } });

Run itIn your own project

npm install @ax-llm/ax

import { ai, ax } from '@ax-llm/ax';

const llm = ai({ name: 'openai', apiKey: process.env.OPENAI_APIKEY! });
const classify = ax('review:string -> sentiment:class "positive, negative, neutral"');

const result = await classify.forward(llm, {
  review: 'Useful and boring in the best way.',
});

Set OPENAI_APIKEY in your environment before running provider-backed code.

In the ax repo

From a clone of the ax repo:

npm run example -- typescript src/examples/typescript/mcp/native-mcp-tools.ts

Active practice

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Answer 2 in a row to learn this · attempt 1

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