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Connect Accident Investigation Prover to ChatGPT and Claude

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Forces systemic root cause analysis beyond simple blame.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 1 capability

We ship only the actions that matter.

Capability set01 / 01

01

1 capability in this set.

Part of 1 available through Accident Investigation Prover.

  1. 01

    Validate accident investigation

    Call this capability before finalizing any investigation conclusion. It forces a five-part analysis: First, correlate evidence by cross-referencing FDR parameters, CVR transcripts, ATC radar tracks, maintenance logs, and wreckage analysis. Second, construct a causal chain, identifying the probable cause and all contributing factors using the NTSB format. Third, classify every factor using the four levels of the HFACS taxonomy. Fourth, analyze organizational factors like scheduling pressure and training budget. Finally, write recommendations that are specific, measurable, addressed, tracked, and evidence-linked. Use this capability once per investigation analysis.

Real work

What teams actually run

01

Engine Failure Analysis

Investigate an uncontained engine failure by tracing the root cause to cost-driven supplier selection and gaps in part traceability.

02

Controlled Flight Into Terrain (CFIT)

Analyze a terrain impact by identifying failures in crew qualification programs and inadequate crew pairing for high-risk airports.

03

Fatigue and Operational Error

Determine if an accident was caused by pilot fatigue or if the primary cause was regulatory gaps, such as insufficient audit frequency.

04

Systemic Safety Audit

Run a full audit on an operation to ensure all five axes—evidence, causal, human factors, organizational, and recommendations—are fully covered.

Automate a task

Put Accident Investigation Prover to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

Accident Investigation Prover works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put Accident Investigation Prover to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

967ms average. Fast in production.

Accident Investigation Prover is checked daily against the live service.

Daily averagePeak 1047ms
Oct 3Today
Fastest day
763ms
Slowest day
1047ms
14-day trend
Slowing+17%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 1 capability arrives ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Accident Investigation Prover, so you can see the experience inside your AI.

It does not authenticate your account with Accident Investigation Prover. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Accident Investigation Prover Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_lW5eq02uyQWDJiNGsxX901icN7Fl8AQ8SwMOpToG/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  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.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "accident-investigation-prover-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_lW5eq02uyQWDJiNGsxX901icN7Fl8AQ8SwMOpToG/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up Accident Investigation Prover in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Accident Investigation Prover owners hand off.

This MCP is built for technical safety professionals who need more than just a simple cause-and-effect report. If your job requires adherence to ICAO Annex 13 or NTSB standards, this capability forces the depth required to prevent recurrence.

  • 01

    Aviation Safety Investigator

    Use it to validate findings and ensure your report meets the highest standards of systemic rigor.

  • 02

    Accident Reconstruction Engineer

    Run complex scenarios to trace failures back through maintenance, training, and regulatory gaps.

  • 03

    Airline Safety Manager

    Validate internal accident reports to ensure they address organizational weaknesses, not just pilot error.

FAQ

Questions Accident Investigation Prover owners ask.

  • 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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