A
licenseNot graded
qualityF
maintenanceThe Comfy MCP Server uses the FastMCP framework to generate images from prompts by interacting with a remote Comfy server, allowing automated image creation based on workflow configurations.
35 PyPI
46
MIT
Local GPU Imagegen
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TDQS
B3.4/5.0
Scored across 17 tools
Disambiguation5/5
Each tool has a clearly defined role in the local GPU image generation pipeline, from environment checks to run finalization. The two generation tools (generate_image and generate_round) are distinct, with one serving as a compatibility fallback and the other as part of the core workflow.
Naming Consistency5/5
All tools follow a strict 'local_gpu_<verb>_<noun>' convention using snake_case. The pattern is uniform and predictable, making it easy to deduce tool behavior from the name alone.
Tool Count4/5
At 17 tools, the set is slightly above the typical 3-15 range, but the complexity of the domain (workflow inspection, trust management, run lifecycle, and mask handling) justifies the count. Each tool serves a distinct purpose, so the overhead is acceptable.
Completeness4/5
The toolset provides end-to-end coverage for managing local GPU image generation runs, including setup, registration, recommendation, execution, review, and cleanup. Minor gaps exist, such as no explicit list-runs tool and no update operation for run fields, but these are not critical given the immutable nature of runs.
Maintenance
ActivityMaintained
ResponsivenessNo issues