A
licenseB
qualityB
maintenanceEnables AI agents to submit GPU job requests, select eligible workers, track execution, and retrieve results via MCP.
14
21
MIT
agent-gpu-pool
by AlfredQuan
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TDQS
B3/5.0
Scored across 13 tools
Disambiguation4/5
The tools separate into clear functional areas: job lifecycle, artifacts/results, and pool/quota administration. Slight overlap exists among list_jobs, list_ready_results, and get_project_runs, where run/result/job terminology could cause misselection, but the descriptions clarify the intended use.
Naming Consistency4/5
Almost every tool uses a verb_noun snake_case pattern such as submit_job, list_jobs, cancel_job, and fetch_artifact. pool_overview breaks the pattern as noun_noun, so the convention is consistent but not perfectly uniform.
Tool Count5/5
Thirteen tools is a well-scoped size for a GPU pool and experiment management server. Each tool covers a distinct workflow step with no obvious redundant entries.
Completeness4/5
The set covers the core experiment lifecycle: submit, list, get, cancel, logs, artifacts, and recorded results, along with worker and quota visibility. Minor conveniences such as a dedicated quota getter or result update tool are absent, but agents can accomplish the intended workflows with the current surface.
Maintenance
ActivitySlowing
ResponsivenessNo issues