`experiment_results`

Pack: ai-model-experiments · Connect: https://pipeworx.io/mcp (see Connect below for a single-pack URL)

No MCP client? Call it directly: GET https://gateway.pipeworx.io/v1/tools/experiment_results for the schema, then POST the same URL with its arguments for the data.

Results of an experiment: per-model aggregates (mean latency, tokens, total billed cost, error rate), per-cell outputs, and the AI-written summary comparing how the models differed (if enabled). Use include_outputs:false for aggregates only. Example: experiment_results({ experiment_id: ”…” })

Parameters

Name	Type	Required	Description
`experiment_id`	string	yes	From experiment_create
`include_outputs`	boolean	no	Include full model outputs per cell (default true)

Example call

Arguments

{
  "experiment_id": "exp_abc123def456"
}

curl

curl -X POST https://gateway.pipeworx.io/ai-model-experiments/mcp \
  -H 'Content-Type: application/json' \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"experiment_results","arguments":{"experiment_id":"exp_abc123def456"}}}'

TypeScript (@pipeworx/sdk)

import { Pipeworx } from '@pipeworx/sdk';
const pipeworx = new Pipeworx();

const result = await pipeworx.call('experiment_results', {
  "experiment_id": "exp_abc123def456"
});

More examples

{
  "experiment_id": "exp_abc123def456",
  "include_outputs": false
}

Connect

Add this to your MCP client config — every tool in the catalog, including this one — or use one-click install buttons:

{
  "mcpServers": {
    "pipeworx": {
      "url": "https://pipeworx.io/mcp"
    }
  }
}

Connect to just the ai-model-experiments pack

{
  "mcpServers": {
    "ai-model-experiments": {
      "url": "https://gateway.pipeworx.io/ai-model-experiments/mcp"
    }
  }
}

See Getting Started for client-specific install steps.

experiment_results