A
licenseNot graded
qualityD
maintenanceEnables AI agents to generate images and videos through natural language by exposing ComfyUI workflows as parameter-configurable MCP tools.
9
MIT
comfyops-mcp
by sandraschi
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TDQS
A3.5/5.0
Scored across 8 tools
Disambiguation4/5
Most tools map cleanly to a distinct resource or action: generation, workflow definitions, models, nodes, generation history, and UI cards. The main boundary overlaps are comfy_agentic_assist vs comfy_generate and comfy_models health vs show_comfyops_status_card, but the descriptions and operation parameters give enough guidance for an agent to choose correctly.
Naming Consistency4/5
The core tools share a predictable comfy_ prefix and snake_case style, with each comfy_<domain> tool using an operation parameter to select actions. The show_*_card presentation tools and comfy_agentic_assist deviate from the resource-manager pattern, but the naming remains readable and mostly consistent.
Tool Count5/5
Eight tools is a well-scoped size for a ComfyUI operations server; each tool covers a meaningful area such as generation, workflow registry, model management, node resolution, generation history, agentic orchestration, and UI display. The operation-based design keeps the tool count from ballooning while still exposing the needed functionality.
Completeness4/5
The core generation lifecycle is covered end-to-end: discover/register workflows, resolve nodes, manage models, generate, browse history, and display results. Gaps such as deleting/uninstalling workflows/models/nodes and an explicit library record operation keep it from being fully complete, but agents can work around these for typical generation tasks.
Maintenance
ActivityActive
ResponsivenessNo issues