Kite Line Tangle Risk Assessment

Kite Line Tangle Risk Assessment MCP Connector for Claude

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Predictive engine for calculating kite line entanglement probability.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner

This MCP server provides a predictive assessment engine to calculate the probability of kite line entanglement. It models the interaction between kite lines, wind behavior, and human movement using a collision and proximity model. Users can use calculate_risk_score to get a normalized risk metric, identify_high_risk_zones to map dangerous geographic areas, generate_avoidance_strategies for actionable safety advice, and analyze_collision_probability for a detailed mathematical breakdown of spatial overlap.

kite-surfingrisk-assessmentwind-safetycollision-predictionmarine-sports

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

calculate_risk_score

Provides a single, normalized risk metric for a specific scenario

generate_avoidance_strategies

Provides actionable advice to mitigate the specific risks calculated

identify_high_risk_zones

Maps specific geographic areas where entanglement is most likely to occur

analyze_collision_probability

Detailed mathematical breakdown of the spatial overlap probability between kite lines

See how to talk to your AI agent using Kite Line Tangle Risk Assessment.

What is the risk score for 15 kites in a freestyle style with high wind variability (0.8) and average rider skill (5)?

The calculated risk score is 8.5, which is classified as Extreme risk due to high wind variability and freestyle movement.

Identify high-risk zones for 10 kites with this beach layout: {"boundary": "shoreline"} and density map: [{"coords": "0,0", "density": 5}]

High-risk zones identified: Zone ID 1, Risk Severity: High, Description: Narrow corridor near the shoreline.

Give me safety strategies for a risk score of 7.

Increase distance between riders and move to lower-density beach sectors to mitigate entanglement risk.

The `calculate_risk_score` tool uses kite count, riding style, wind variability, and rider skill to produce a normalized score from 1 to 10.

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