Bow-Tie Risk Analysis Engine

Bow-Tie Risk Analysis Engine MCP Connector for Claude

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A quantitative risk assessment engine for modeling threats, top events, and consequences using bow-tie analysis.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner

This MCP server provides a mathematical and visual framework for risk assessment. It allows AI agents to model the relationship between hazards, threats, and consequences. Using tools like analyze_threat_path and analyze_consequence_path, agents can evaluate how preventive and mitigative barriers affect risk likelihood and severity. The engine also includes evaluate_barrier_health to account for degradation factors and calculate_risk_reduction_profile to provide a high-level summary of total risk reduction.

risksafetybow-tiequantitativeassessment

4 tools expose this connector's capabilities to your AI agent.

analyze_threat_path

Evaluates the relationship between a specific threat and the top event, accounting for preventive barriers

calculate_risk_reduction_profile

Provides a high-level summary of how much risk is reduced by the current set of barriers

analyze_consequence_path

Evaluates the relationship between the top event and a consequence, accounting for mitigative barriers

evaluate_barrier_health

Assesses the current capability of a specific barrier by considering its degradation

See how to talk to your AI agent using Bow-Tie Risk Analysis Engine.

Analyze the threat path for threat 'T-101' leading to top event 'TE-202' using preventive barriers 'B-01' and 'B-02'.

The threat likelihood for T-101 is 0.8. After applying barriers B-01 and B-02, the residual threat likelihood is reduced to 0.15, and the path is successfully blocked.

What is the current health status of barrier 'B-500'?

Barrier B-500 has a nominal effectiveness of 0.95, but due to degradation, its current effectiveness is 0.72. The status is currently 'Degraded'.

Calculate the risk reduction profile for top event 'TE-99'.

For top event TE-99, the unmitigated risk score is 100.0 and the mitigated risk score is 12.5, resulting in a total reduction percentage of 87.5%. No critical gaps were identified.

The engine uses `evaluate_barrier_health` to assess how degradation factors reduce a barrier's nominal effectiveness, providing a real-time view of current capability.

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