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.

11 focused minutesNot started

Worked example

See the idea in context

client.init();
String taskId=String.valueOf(castMap(client.callTool("start_reindex",Map.of("scope","all")).get("task")).get("taskId"));
source.start(event->runtime.publish(event,source.identityScope(),source.trust()));

Run itIn your own project

// Gradle (build.gradle):
implementation 'dev.axllm:ax:22.0.4'
// Maven (pom.xml):
<dependency>
  <groupId>dev.axllm</groupId>
  <artifactId>ax</artifactId>
  <version>22.0.4</version>
</dependency>

import dev.axllm.ax.Ax;

var llm = Ax.ai("openai", Map.of("apiKey", System.getenv("OPENAI_API_KEY")));
var classify = Ax.ax("review:string -> sentiment:class \"positive, negative, neutral\"");

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 -- java src/examples/java/mcp/NativeMCPToolsExample.java

Active practice

Show that you can use it

Answer 2 in a row to learn this · attempt 1

Keep exploring

See the idea in context

Show that you can use it

Source-backed follow-up