relaygpu-mcp
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TDQS
Scored across 14 tools
Tools are largely distinct and the descriptions explicitly cross-reference their partners (run_model → check_task, run_workflow → check_workflow_run), which resolves most ambiguity. The only soft overlaps are the account/money trio get_pricing, estimate_cost, get_usage and get_credits, which an agent could momentarily confuse, plus the parallel check_task/check_workflow_run pair that requires reading descriptions to separate.
Every tool follows a strict snake_case verb_noun pattern (list_workflows, search_models, get_model, run_model, check_task, cancel_workflow_run, upload_file, estimate_cost). The run/check/cancel triplet for workflows and the run/check pair for tasks are named symmetrically, reinforcing the pattern.
14 tools sit squarely in the well-scoped range for an inference/media platform. Each tool maps to a distinct stage: discovery, schema lookup, pricing, execution, polling, cancellation, upload, and account state, with no obviously redundant entries.
The surface covers the full lifecycle for models and workflows: discover → inspect schema → estimate cost → run → poll → cancel → store outputs, plus upload, usage, credits, and docs. The notable gap is asymmetry in cancellation: workflow runs can be cancelled but async model tasks (check_task) have no cancel or list/history operation, which could strand long-running or unwanted tasks.