"WhyLabs AI Observability Platform" matching MCP connectors:

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).

Free platform to test MCP clients without installing anything. Create mock tools with dynamic templates, configurable delays, conditions (if/then), and response sequences. Supports JSON-RPC 2.0 over Streamable HTTP. Built-in text_echo and json_echo tools. Rate-limited tiers: anonymous (5 calls/min, 1 mock tool), registered (10 calls/min, 4 mock tools), premium (60 calls/min, unlimited). Zero setup — no install, no registration required. More info: https://www.testmcp.dev

Check that your AI is being logical. Free tool that mathematically catches contradictions in agent reasoning. No account needed. Also offers paid guardrails that converts natural language to formal verification proofs, that anyone can check succinctly.

Hire a real human for real-world verification, product testing, AI output review, and errands.

Deterministic validation for AI-generated artifacts: JSON Schema, OpenAPI response, SQL syntax.

Webhook relay for AI agents: keyless quickstart, event inspection, replay, mock payloads.

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

Promotion gate for AI agents: leakage audits, exact-statistics verdicts, and a live report card.

Voice-powered bug reporting with 13 MCP tools. Record bugs by talking; let AI find and fix them.

Check AI work against requirements and return structured verdicts, findings, and repair steps.

Generate realistic, FK-consistent synthetic test data for your databases from your AI assistant.

Generate deterministic placeholder image URLs and packs for docs, staging, testing, and AI agents.

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

AI website growth audits: SEO, performance, AI readiness (GEO), conversion, a11y, security.

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

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

Scan URLs for WCAG 2.1 violations, generate AI fixes, and produce VPAT 2.5 compliance reports.

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

Deterministic recipe verification engine — validates AI-generated recipes against master SOPs.

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