RunComfy MCP

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by runcomfy-com

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Python

Hybrid

get_model_request_result

Read-onlyIdempotent

Fetch the result of a completed model API request by request ID, including output data and hosted asset URLs.

Instructions

Fetch a completed Model API request's outputs.

Backs ``GET /v1/requests/{request_id}/result``. The ``output`` shape
is defined by the model's Output schema; any hosted asset URLs found
in it are also flattened into ``output_urls``.

This is for ``run_model`` requests. Serverless deployment requests
use ``get_request_result`` instead.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "request_id": "<request_id>"
    },
    "name": "get_model_request_result"
  }
}

Input Schema

Name	Required	Description	Default
`request_id`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.1.0Sep 7, 2026

TDQS

A4.7/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is covered. The description adds useful behavioral detail beyond annotations: the output shape follows the model's Output schema, and hosted asset URLs are flattened into output_urls. This informs the agent about the response structure without contradicting the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded, with each sentence serving a distinct purpose: primary action, output/behavior detail, and usage scoping relative to a sibling. There is no filler or repetition of schema information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given a single obvious parameter, rich read-only annotations, and no output schema, the description is complete. It covers the endpoint, the output shape, the output_urls flattening behavior, and the sibling alternative, which is everything an agent needs to correctly invoke this tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema offers only a bare 'request_id' string with no description, so the description must compensate for 0% schema coverage. The description does this by showing request_id in the endpoint path and explaining that it refers to a run_model request. This gives the agent enough semantic understanding to select and supply the correct ID, even if it doesn't detail how to obtain that ID.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a precise verb and object: 'Fetch a completed Model API request's outputs.' It clearly names the underlying endpoint and distinguishes this tool from the closely related sibling get_request_result by specifying it covers run_model, not serverless, requests. This leaves no ambiguity about what the tool does.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states this tool is for run_model requests and explicitly routes serverless deployment requests to get_request_result instead. It also signals that it should be used for completed requests, giving the agent clear conditions for when this tool is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.