comfy-mcp

Featured

Create and inspect generative media projects in the Comfy MCP Harness workspace, including its local starter and optional upstream integration.

AI & Automation 957 stars 79 forks Updated today MIT

Install

View on GitHub

Quality Score: 91/100

Stars 20%
99
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
96
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Variation garden Read `studio.json` to understand the current controls; `"$STUDIO_TOOLCHAIN/../studio.config.json"` describes their ranges. Run `"$STUDIO_TOOLCHAIN/run.sh" generate` to make a new result. Successful artifacts and their measurements are in `out/runs/<id>/`; `out/latest.json` names the current result. A failed run preserves the last success and records the error in the verdict. The local starter creates deterministic procedural SVG artwork and a contact sheet. It is not diffusion or an AI-generated image claim. The native action submits the saved API workflow to an existing local ComfyUI, polls its result, and collects actual output images. The supplied native workflow uses no model and no paid API. Use `"$STUDIO_TOOLCHAIN/../README.md"` for the integration contract and commands. Read the relevant files under `$STUDIO_UPSTREAM` before using an upstream API. Keep controls within their documented ranges, preserve the data needed to reproduce a comparison, and distinguish preview results from native service or hardware output. The viewer supports history and artifact downloads; tell the user which run contains the result, and what was actually measured. ## Grow a reproducible family Choose a palette and seed, run `generate`, then inspect each study and its saved recipe. The SVG hashes verify reproducibility. These local vector studies do not use a diffusion model. Keep selected studies and their seed/parameters together when making a new family. For an inst...

Details

Author
autonomous-ai
Repository
autonomous-ai/openharness
Created
1 months ago
Last Updated
today
Language
C
License
MIT

Similar Skills

Semantically similar based on skill content — not just same category