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comfy-h3-mcp

comfy-h3-mcp

by jonpojonpo
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

job_preview

Preview a completed H3 job by viewing a contact sheet of frames sampled across the clip and listening to its soundtrack, enabling judgment of results before iterating on the prompt.

Instructions

Look at and listen to a finished H3 job.

MCP has no video content type, so this returns a contact sheet of frames sampled evenly across the clip (viewable as an image) plus the soundtrack as audio. Use it to actually judge a result before iterating on the prompt.

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": {
      "prompt_id": "<prompt_id>"
    },
    "name": "job_preview"
  }
}

Input Schema

NameRequiredDescriptionDefault
rowsNo
columnsNo
prompt_idYes
tile_widthNo
include_audioNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

Discloses that MCP has no video content type, so the tool returns a contact sheet of frames plus audio instead. This is important behavioral context not available from annotations (which are absent). It implies a read-only operation and describes the return format.

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?

Two concise paragraphs with the purpose in the first sentence. The additional details about the output format and usage context are relevant and not redundant.

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

Completeness4/5

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

Given no output schema, the description explains the return format (contact sheet + audio) and the reason for this design. It doesn't describe each parameter in detail, but the tool is relatively simple and the core behavior is covered.

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

Parameters2/5

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

The schema has no parameter descriptions (0% coverage), and the description does not explain the meaning of rows, columns, tile_width, or include_audio. Parameter names are somewhat self-explanatory, but the description adds no detail, leaving the agent to infer from names alone.

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 clearly states the tool's purpose: to look at and listen to a finished H3 job. It differentiates from siblings like job_status and job_cancel by focusing on previewing results and explains the output format.

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

Usage Guidelines4/5

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

Explicitly says to use it to judge a result before iterating on the prompt, indicating appropriate timing. It does not name alternatives or when-not-to-use scenarios, but the context is clear enough for selection.

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

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