Run Parallel AI Research

For a researcher who needs several structured briefs at once. It creates a Parallel AI task group, launches a long running research run per topic, watches progress, and collects the structured outputs.

PAParallel AI

The grind

Research at scale is painful

Here's what doing this by hand looks like today, and why it doesn't scale.

Running ten research passes one after another takes the whole afternoon.
Every brief comes back in a different shape, so synthesis becomes a second job.
You would batch them if there were a tool that ran parallel runs and collected structured output.

MewCP collapses all of this into one prompt. Here's what that looks like.

The flow

6 steps · 1 server

Your agent runs it end-to-end

Create a Parallel AI task group for the batch.

For each topic, start a research run with your structured output schema.

Poll the task group until every task reaches a terminal state.

Fetch each completed task's structured output.

Aggregate the results into a Google Doc or Sheet if an output target is set.

Return the aggregated link and the per task status.

The payoff

Ten briefs at once, same structure

Launch a batch and collect structured outputs across every topic, with no sequential grind and no inconsistent formatting.

Paste this into Claude, Codex, or any MCP-connected agent. It'll connect your apps and run the task from start to finish.

Run it yourself

Copy the prompt

prompt

Goal: Run Parallel AI Research

MCP servers needed (connected through MewCP): Parallel AI

Steps:
1. Create a Parallel AI task group for the batch.
2. For each topic, start a research run with your structured output schema.
3. Poll the task group until every task reaches a terminal state.
4. Fetch each completed task's structured output.
5. Aggregate the results into a Google Doc or Sheet if an output target is set.
6. Return the aggregated link and the per task status.

Check with me before sending any message or changing data in a connected app.

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