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comfygenmcp

by aschet
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

generate_image

Create images from text prompts by running a saved ComfyUI workflow, then get the result inline with a shareable URL.

Instructions

Generate an image on ComfyUI and return it inline.

Returns " · seed · " plus -- unless this server was started with --no-inline-image -- the image itself.

Clients usually collapse tool results, so the image is easy to miss. Pass the URL on in your reply: it survives the collapse, and is how the user sees the picture when no image is returned. Write it bare so the client turns it into a link -- code formatting or backticks make it unclickable.

Use exactly the workflow name the user asked for. Similar names are different workflows -- "Krea2" and "Krea2+Upscale" are not interchangeable.

Fails if the workflow needs an input image or has no prompt node to patch.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedNoReuse a seed from an earlier result to reproduce it. Omit for a new one.
promptYesWhat to draw, in plain language.
workflowYesName of a workflow saved in ComfyUI, exactly as list_workflows returns it. If you do not have a name yet, call list_workflows and use the first ready one rather than asking the user to choose.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so thoroughly. It discloses the exact return format, the inline image behavior under --no-inline-image, client collapse behavior, URL formatting requirements, and failure modes. This is far beyond minimal transparency.

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 front-loaded with the primary purpose, then systematically covers return format, client behavior, URL handling, workflow matching, and failure conditions. Although it is moderately long, every sentence provides actionable information with no filler.

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?

There is no output schema, so the description fully explains the return value and its nuances. It also covers server configuration, client UI behavior, and failure conditions. No critical operational detail is missing for an agent to invoke the tool successfully.

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?

Schema coverage is 100%, so baseline is 3. The description adds meaningful context for the workflow parameter: exact name as returned by list_workflows, directive to call list_workflows if unknown, and warning that similar names are not interchangeable. This extra guidance justifies a 4.

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 generates an image on ComfyUI and returns it inline. The verb 'generate' and resource 'image' are specific, and it is easily distinguished from the only sibling list_workflows, which is a prerequisite rather than an alternative.

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 provides explicit guidance on when to call list_workflows first (when no workflow name is known) and warns about exact workflow-name matching. It also states failure conditions (workflow needs input image or lacks a prompt node), giving clear when-not-to-use information.

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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