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New in version 2.14.0 The MCP task protocol 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 for how to enable this on the server side.

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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. 
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: 
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)

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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. 
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: 
# 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().

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Real-Time Status Updates

Register callbacks to receive status updates as the server reports progress. Both sync and async callbacks are supported. 
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)

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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. 
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.

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Complete Example

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())