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. rust academy academy/topics/mcp-tasks-advanced website/content-src/academy/course.mjs academy Handle long-running MCP work
ax
Rust axllm
TypeScript Python Java C++ Go Rust
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

.call_tool("start_reindex", json!({"scope":"all"}))?;
source.start()?;
source.poll();
Run itIn your own project
cargo add axllm

use axllm::{ai, ax};
use serde_json::json;

let llm = ai("openai", json!({"apiKey": std::env::var("OPENAI_API_KEY")?}))?;
let classify = 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 -- rust src/examples/rust/mcp/native_mcp_tools.rs
Active practice

Show that you can use it

Answer 2 in a row to learn this · attempt 1
Keep exploring

Source-backed follow-up