"Troubleshooting Cloudflare Infrastructure for App Issues" matching MCP connectors:

Drive real Android & iOS devices and web browsers from natural language for mobile + web QA. 145+ tools across device control, app management, automation sessions, browser automation, and flow recording / replay. Bearer-auth — get a token at robotactions.com → Profile → API Tokens.

Moderated usability testing: read sessions, notes, transcripts, reports, and draft test scenarios.

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).

Conformance checker for MCP servers. Free, no key, verdicts recomputable and re-measured daily.

Deterministic dataset-quality verdict, score and per-check facts for AI agents. No LLM.

A webhook inbox for agents: one call returns a live URL. Mock, verify, inspect and replay.

Preflight QA for AI-agent deliverables with structured verdicts and repair guidance.

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

Pre-execution governance for AI agents. Deterministic PASS/FAIL/REVIEW verdicts, replayable proof.

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

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

One-cent x402 and MCP readiness checks plus fixed-price marketplace launch packs.

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

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

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

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.

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

Adversarial behavioural-bias engine — audits your decisions for cognitive biases via your own AI.