MCP For Claude Marketplace
AI Safety Evaluation Score

AI Safety Evaluation Score MCP Connector for Claude

A+

Translates technical AI safety metrics into financial risk profiles and safety posture scores.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner
More Details Connect to Claude

This MCP server provides institutional investors with a specialized assessment engine to quantify AI risk. It converts technical data from safety evaluations, red-teaming, and bias assessments into actionable financial metrics. Use calculate_safety_posture to determine the overall robustness of a model, assess_regulatory_exposure to evaluate legal risks in specific jurisdictions like the EU or USA, and estimate_liability_risk to project potential financial impact based on vulnerabilities and user base size. It also allows for industry-specific comparisons using get_safety_benchmarks.

Available Tools

calculate_safety_posture_tool, assess_regulatory_exposure_tool, estimate_liability_risk_tool, get_safety_benchmarks_tool

riskcompliancesafetyinvestmentaudit

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

calculate_safety_posture_tool

Calculates the overall safety posture score for an AI model

get_safety_benchmarks_tool

Compares a specific model's data against industry standard safety tiers

assess_regulatory_exposure_tool

Determines the likelihood and impact of legal intervention

estimate_liability_risk_tool

Translates safety failures into potential financial liability

See how to talk to your AI agent using AI Safety Evaluation Score.

What is the safety posture for a model with 50 passed evaluations, 2 red-teaming failures, a bias score of 10, and no certifications?

The calculated safety score is 75, which falls into the Robust status level with a high confidence rating.

What is the regulatory exposure for a General Purpose model in the EU with current certification?

The exposure level is Medium, with the EU AI Act being the primary regulatory driver.

Estimate the liability risk for a model with critical red-teaming severity and a systemic bias impact for 1,000,000 users.

The risk magnitude is extremely high, with a potential impact involving significant class-action litigation and regulatory fines.

The score is derived from successful safety evaluations, the severity of red-teaming failures, detected bias, and whether the model holds industry certifications via `calculate_safety_posture`. Tools available: `calculate_safety_posture_tool`, `assess_regulatory_exposure_tool`, `estimate_liability_risk_tool`.

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