JevLab MCP Server
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- AlicenseAqualityAmaintenanceEnables MCP clients to score retrieval quality with recall, precision, nDCG, hit rate and MRR, compare 2-3 configurations with seeded paired-bootstrap confidence intervals, audit agent tool calls against expected traces, and detect prompt regressions against golden sets. It also generates Markdown, JSON or JUnit reports with pass/fail gates, all deterministically and offline without paid API keys.6172 npm1MIT
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- AlicenseNot gradedqualityAmaintenanceServes offline document validation and evaluation operations of the Judgment Pack Specification to MCP clients over stdio, enabling agents to validate and evaluate JPS documents as tool calls. Supports conformance validation, experimental evaluation with disposition and error classes, and corpus testing.2Apache 2.0
- AlicenseNot gradedqualityAmaintenanceExposes three stdio tools that answer typed questions — yes/no, choice, and score — with calibrated probabilities instead of prose, letting any MCP host query a judgment model without a chat interface. Runs fully offline on a synthetic mock by default, with named, per-feature egress disclosure and redaction only when a live provider is explicitly configured.66 npmApache 2.0
TDQS
Scored across 4 tools
Each tool targets a distinct evaluation activity: bias auditing, rubric listing, benchmarking, and calibration. The bias audit and benchmarking tools could be loosely confused as both assess judges, but the descriptions clearly distinguish bias measurement from gold-label benchmarking.
All tools share the jevlab_ prefix and snake_case, but the naming pattern is mixed: jevlab_list_rubrics is verb_noun, jevlab_calibrate is a bare verb, jevlab_bench is a short form, and jevlab_bias_audit is a noun phrase. This is readable but not predictably consistent.
Four tools is a well-scoped set for a focused judge-evaluation toolkit. Each tool covers a distinct core capability without excess or apparent redundancy.
The surface covers the key lifecycle steps for judge auditing: listing rubrics, auditing bias, benchmarking, and calibrating. Minor gaps exist around custom rubric management and fetching individual rubrics, but agents can work around them.