# Mindandrocket (mindandrocket.de): agent-readiness 68/100, grade C > Rank 141 of 1000 on Qomvia (rubric v2.3.0). Last scanned 2026-09-28T13:10:15.830Z. Page: https://qomvia.com/site/mindandrocket-de JSON: https://qomvia.com/api/score/mindandrocket-de ## Summary { "known": false, "confidence": "low", "summary": "I do not have specific pre-existing knowledge about mindandrocket.de. Therefore, I cannot provide a summary of its operations.", "offerings": [], "audience": null, "geography": null, "strengths": [], "unknowns": [ "The specific services or products offered by mindandrocket.de", "Its target audience and market positioning", "Its operational geography and business model", "Its unique selling points or competitive advantages", "Any historical performance or reputation data" ], "alternatives": [], "business": null, "competitors": [] } ## Score by group - Machine access: 24/24 - Content legibility: 21/26 - Discovery surface: 12/20 - Identity & policy: 5/12 - Agent-facing performance: 5/8 - Agent protocols: 1/10 Failing checks: - [blocker] No MCP endpoint to call - [improvement] No stated policy for automated access - [improvement] No machine-readable contact - [improvement] No Content Signals - [improvement] Main content is extractable ## Add-on packs - E-commerce & product feeds: 15/100 (not part of the public score) ## FAQ Q: Is Mindandrocket readable by AI agents? A: Mindandrocket (mindandrocket.de) scores 68 out of 100 for agent readiness, grade C, measured 2 days ago, on 28.09.2026. 0 of 3 agent classes we test can use the site, and 1 check currently block agents outright. Q: What stops agents from using mindandrocket.de? A: The heaviest problems are: No MCP endpoint to call; No stated policy for automated access; No machine-readable contact; No Content Signals; Main content is extractable. Each one is scored from a public HTTP response, and the fix for each is listed in the signed-in report. Q: How is the Mindandrocket agent-readiness score calculated? A: Qomvia fetches public pages of mindandrocket.de as an AI agent would and runs the core checks every site gets across 6 groups: Machine access, Content legibility, Discovery surface, Identity & policy, Agent-facing performance, Agent protocols. Checks are weighted by how much an agent loses when they fail, and the score is expressed out of 100. E-commerce & product feeds checks are scored separately (15/100) and do not affect the public score or rank. Q: How often is this score updated? A: Public scores are re-checked when the site is re-scanned; tracked domains are re-scanned weekly and their owners are alerted when a check regresses. This page shows the scan from 2 days ago, on 28.09.2026. ## Related - Leaderboard: https://qomvia.com/leaderboard - Score another site: https://qomvia.com/