Verbinden Sie Accident Investigation Prover mit Ihrer KI

• 01 / 02Empfehlungen erstellen
• 02 / 02Kausalketten analysieren

Schnellster Tag

763ms

Langsamster Tag

1047ms

14-Tage-Trend

Verlangsamend+17%

Accident Investigation Prover Connector

Alles bereit. Wählen Sie Ihren MCP-Client und folgen Sie den Einrichtungsschritten.

Connector-Linkhttps://edge.vinkius.com/vk_preview_lW5eq02uyQWDJiNGsxX901icN7Fl8AQ8SwMOpToG/mcpKopieren

Claude Desktop

Folgen Sie den Schritten unten, um sich in Sekunden zu verbinden.

1. 1In Claude Desktop, open Settings → Connectors.
2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
3. 3Click Add and start a new chat — Accident Investigation Prover capabilities are ready to use.

Konfiguration · claude_desktop_config.jsonKopieren

{
  "mcpServers": {
    "accident-investigation-prover-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_lW5eq02uyQWDJiNGsxX901icN7Fl8AQ8SwMOpToG/mcp"
    }
  }
}

• Claude
• ChatGPT
• Cursor
• VS Code
• Windsurf
• Claude Code
• JetBrains
• Cline

Schritt-für-Schritt-Anleitungen für jeden Client finden Sie im Guide. Verbinden

Geführte Einrichtung für Claude? Accident Investigation Prover in Claude und anderen KI-Tools einrichten

Alle KI-Clients ansehen, mit denen dieser Connector funktioniert ↑

• 01

  Flugunfallermittler

  Zur Durchführung von Untersuchungen, die über einfache Fehlerzuweisungen hinausgehen und die gesamte Kausalkette nach NTSB/ICAO nachzeichnen.

• 02

  Flugsicherheitsbeauftragte

  Zur Bewertung von Betriebsabläufen und zur Identifizierung organisatorischer Schwachstellen, die zu Sicherheitsrisiken führen können.

• 03

  Luftfahrtregulierungsbehörden

  Zur Überprüfung der Einhaltung internationaler Standards und zur Festlegung von Verbesserungen in der Branche.

• 01

  Does this MCP just tell me who was at fault?

  No. The MCP is designed to prevent assigning blame. It focuses on the systemic failure. It forces the analysis to look at organizational decisions, like scheduling pressure or training gaps, rather than just pilot error.

• 02

  What kind of data does it need to run?

  It requires highly specific data sources, including FDR parameters, CVR transcripts with timestamps, ATC recordings, and detailed maintenance logs. Narrative descriptions alone are insufficient.

• 03

  What is the difference between this and a standard AI prompt?

  A standard prompt accepts a single conclusion. This MCP forces the AI to use the NTSB/ICAO methodology, demanding a causal chain, four-level human factor classification, and evidence correlation across multiple sources.

• 04

  Can it analyze non-aviation incidents?

  The MCP is built around aviation standards (ICAO Annex 13). Its capabilities and methodologies are specific to aviation safety and accident investigation.

• 05

  What does 'HFACS' mean?

  HFACS stands for Human Factors Analysis and Classification System. The MCP uses it to classify every contributing factor into one of four levels: unsafe acts, preconditions, supervision, or organizational issues.

• 06

  How does this prevent 'pilot error' as a root cause conclusion?

  The engine maintains a semantic trap list of blame-language signals: 'pilot error,' 'crew error,' 'human error,' 'judgment error,' 'failed to,' 'negligence.' If the LLM uses any of these in the HFACS taxonomy field, the classification is rejected. Instead, the LLM must classify each factor at the correct HFACS level: Level 1 (what the pilot did. skill error, decision error, perceptual error, or violation), Level 2 (what conditions enabled it. fatigue, CRM failure, environment), Level 3 (what supervision allowed it. scheduling, training gaps), Level 4 (what organizational decisions created it. budget cuts, staffing, regulatory gaps). 'Pilot error' is Level 1 only. the investigation must reach Level 4.

• 07

  What evidence sources must be cross-referenced?

  Five mandatory sources: (1) Flight Data Recorder. minimum 88 parameters per ICAO Annex 6, with timestamps. (2) Cockpit Voice Recorder. last 2 hours of audio, transcribed with timestamps, correlated with FDR parameter changes. (3) ATC recordings. radar track, clearances, handoffs, weather advisories. (4) Maintenance logs. last A/B/C/D checks, MEL items, deferred defects, AD compliance, component life (TSN/TSO/CSN/CSO). (5) Wreckage analysis. impact signatures, fire patterns, fracture analysis (fatigue vs overload), metallurgical examination. The engine rejects speculative language like 'it appears that' or 'evidence suggests' when hard data from these sources exists.

• 08

  Why does this require recommendations to be addressed to specific authorities?

  Because 'improve training' with no addressee has zero accountability. The NTSB model requires each recommendation to name the authority responsible for implementation. the FAA, the operator, the manufacturer, or an international body. Each recommendation must include: what specific action to take, measurable success criteria, a response deadline (typically 90 days), a verification mechanism (audit, inspection, data review), and a direct link to a specific investigation finding. This is how aviation achieved its extraordinary safety record. not through vague wishes, but through tracked, accountable, evidence-linked changes.

• 

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Vorschläge

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• 

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