"Understanding the Concept of LLM Context" matching MCP connectors:

Prompt evals over MCP: run a prompt on your dataset, score each output 1-5 with an LLM judge.

Evidence-gated task verification for AI agents. Decompose goals into acceptance criteria, attach proof (screenshot, curl, file), independent LLM judge accepts or rejects. 24 tools. Hosted remote MCP (streamable-http, OAuth 2.1 + DCR).

Verify scraped data against the live source page. Signed verdicts, $0.01 via x402.

Post-scrape data cleaner, no LLM: repairs mojibake, HTML, invisible chars. Plus a verdict.

Estimated game fps for any GPU or Apple Silicon chip, with the limiter and tweaks.

Grade MCP servers A to F with the open behavioral litmus. npm: full toolset; hosted: lookups only.

Check if your MCP server is ready to publish on the MCP Registry, Smithery, or npm.

Runs your code against a contract; returns HELD or BROKE at the exact input. Deterministic.

Read-only MCP server for the OPERANT AI operating-agent calibration benchmark.

Machine-readable taxonomy of 100+ AI system failure modes spanning factuality, alignment, planning, code generation, and instruction following.

Test the voice agents you run: scored transcripts, pass/fail verdicts, latency and WER metrics.

MCP server for the Fail Modes taxonomy — a knowledge base of AI system failure modes

A flock of AI users tests your deployed app and reports where real people get stuck, with fixes.

MCP-native AI evaluation: rubric audits, eval suites, and proof reports for AI/LLM output.

PQS scores any prompt before the model runs. 8 dimensions. 5 frameworks. Pre-flight, not post-hoc.

The world's first named AI prompt quality score. Score, optimize, and compare LLM prompts before they hit any model. Free tier available. Built on PEEM, RAGAS, G-Eval, and MT-Bench frameworks. x402-native on Base.

MCP server for static security analysis of Android source code

Control real Android and iOS devices with LLM agents — tap, swipe, type, automate flows.

MCP server providing access to the Scorecard API to evaluate and optimize LLM systems.

Pay-per-call AI evaluation MCP server. Score LLM outputs against benchmark rubrics via Workers AI.