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licenseA
qualityC
maintenanceA local MCP server that packages LLM evaluation gates as reusable CI/CD primitives, enabling AI agents to run datasets against models, score responses, and enforce quality thresholds.
10
MIT
No user-submitted related servers found.
Scored across 3 tools
Each tool has a distinct purpose: running evaluations, comparing results, and applying deployment policy. There is no overlap.
All tools follow a consistent verb_noun pattern (run_evaluation_suite, compare_regression, decide_canary), making them predictable.
With 3 tools, the server covers the core evaluation workflow without being bloated. Slightly minimal but appropriate for a focused server.
The tools cover the main lifecycle: run suite, compare results, decide promotion. Minor gaps like suite management exist, but the core workflow is complete.