Progress Monitoring

everyrow operations typically take 1–10+ minutes depending on dataset size and operation type. Both the Python SDK and the MCP tools provide progress monitoring and a session URL where you can watch tables update in real-time.

What to Expect

Web UI

Every operation is part of a session, which you can view at https://futuresearch.ai/sessions/<session_id>. You can open it in your browser to see:

• Real-time progress for each row
• Web searches each agent ran and the pages it read
• Explanation for each result, including links to sources
• Data visualizations

Python SDK

To see progress updates while a task is running, use the print_progress callback:

from everyrow import print_progress

result = await task.await_result(on_progress=print_progress)

Output:

 0/10   0% | 10 running
 2/10  20% |  8 running
 4/10  40% |  6 running
 6/10  60% |  4 running
 8/10  80% |  2 running
10/10 100%

You can also provide a custom on_progress callback for programmatic progress handling (see below).

MCP Tools

When you run an everyrow operation via MCP:

1. The tool returns immediately with a session URL
2. Progress updates appear every few seconds during execution
3. Results are saved as a CSV file when the operation completes
4. If you've installed the plugin, a desktop notification (macOS and Linux) tells you when it's done

The workflow:

everyrow_agent        →  start the operation, get a task_id and session URL
everyrow_progress     →  check status (blocks for a few seconds, then returns progress)
everyrow_progress     →  check again (the agent loops automatically)
everyrow_results      →  download results when complete

The agents handle the polling loop automatically. You'll see progress in the conversation like:

Running: 20/50 complete, 30 running (45s elapsed)

And when it finishes:

Completed: 50/50 (0 failed) in 100s
...
Saved 50 rows to /path/to/output.csv

Python SDK Progress

For printing progress updates as a task runs, use the provided print_progress callback:

from everyrow import print_progress

result = await task.await_result(on_progress=print_progress)

Or provide a custom callback:

from everyrow.generated.models import TaskProgressInfo

def my_progress_handler(progress: TaskProgressInfo):
    print(f"{progress.completed}/{progress.total} done, {progress.failed} failed")

result = await task.await_result(on_progress=my_progress_handler)

The callback receives a TaskProgressInfo object and only fires when the progress snapshot changes.