--- title: Background Tasks sidebarTitle: Background Tasks description: Execute operations asynchronously and track their progress icon: clock tag: "NEW" --- import { VersionBadge } from "/snippets/version-badge.mdx" The [MCP task protocol](https://modelcontextprotocol.io/specification/2025-11-25/basic/utilities/tasks) lets you request operations to run asynchronously. This returns a Task object immediately, letting you track progress, cancel operations, or await results. See [Server Background Tasks](/v2/servers/tasks) for how to enable this on the server side. ## Requesting Background Execution Pass `task=True` to run an operation as a background task. The call returns immediately with a Task object while the work executes on the server. ```python from fastmcp import Client async with Client(server) as client: # Start a background task task = await client.call_tool("slow_computation", {"duration": 10}, task=True) print(f"Task started: {task.task_id}") # Do other work while it runs... # Get the result when ready result = await task.result() ``` This works with tools, resources, and prompts: ```python tool_task = await client.call_tool("my_tool", args, task=True) resource_task = await client.read_resource("file://large.txt", task=True) prompt_task = await client.get_prompt("my_prompt", args, task=True) ``` ## Working with Task Objects All task types share a common interface for retrieving results, checking status, and receiving updates. To get the result, call `await task.result()` or simply `await task`. This blocks until the task completes and returns the result. You can also check status without blocking using `await task.status()`, which returns the current state (`"working"`, `"completed"`, `"failed"`, or `"cancelled"`) along with any progress message from the server. ```python task = await client.call_tool("analyze", {"text": "hello"}, task=True) # Check current status (non-blocking) status = await task.status() print(f"{status.status}: {status.statusMessage}") # Wait for result (blocking) result = await task.result() ``` For more control over waiting, use `task.wait()` with an optional timeout or target state: ```python # Wait up to 30 seconds for completion status = await task.wait(timeout=30.0) # Wait for a specific state status = await task.wait(state="completed", timeout=30.0) ``` To cancel a running task, call `await task.cancel()`. ### Real-Time Status Updates Register callbacks to receive status updates as the server reports progress. Both sync and async callbacks are supported. ```python def on_status_change(status): print(f"Task {status.taskId}: {status.status} - {status.statusMessage}") task.on_status_change(on_status_change) # Async callbacks work too async def on_status_async(status): await log_status(status) task.on_status_change(on_status_async) ``` ## Graceful Degradation You can always pass `task=True` regardless of whether the server supports background tasks. Per the MCP specification, servers without task support execute the operation immediately and return the result inline. The Task API provides a consistent interface either way. ```python task = await client.call_tool("my_tool", args, task=True) if task.returned_immediately: print("Server executed immediately (no background support)") else: print("Running in background") # Either way, this works result = await task.result() ``` This means you can write task-aware client code without worrying about server capabilities. ## Complete Example ```python import asyncio from fastmcp import Client async def main(): async with Client(server) as client: # Start background task task = await client.call_tool( "slow_computation", {"duration": 10}, task=True, ) # Subscribe to updates def on_update(status): print(f"Progress: {status.statusMessage}") task.on_status_change(on_update) # Do other work while task runs print("Doing other work...") await asyncio.sleep(2) # Wait for completion and get result result = await task.result() print(f"Result: {result.content}") asyncio.run(main()) ```