MCP For Claude Marketplace
AI Improvement Velocity Tracker

AI Improvement Velocity Tracker MCP Connector for Claude

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Quantify the speed and effectiveness of your AI model improvement cycles.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner
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This MCP server provides tools to measure how effectively an AI product evolves based on user input. It calculates the Feedback Velocity Score, implementation rates, and improvement latency to help teams understand the efficiency of their feedback loops. Use get_velocity_summary for high-level performance overviews, calculate_feedback_efficiency to analyze implementation success, analyze_improvement_latency to measure time delays, and get_satisfaction_metrics to correlate model changes with user sentiment.

feedback-loopai-velocitymodel-improvementuser-sentimentefficiency-metrics

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

get_satisfaction_metrics

Pass both improvement rate and implementation percentage. Correlates model improvements with user sentiment

get_velocity_summary

Use this to check overall system health. Provides a high-level overview of the current AI improvement performance

analyze_improvement_latency

Ensure both rate and time metrics are provided. Measures the time delay in the improvement loop

calculate_feedback_efficiency

Provide all three required metrics. Analyzes how effectively the team is turning raw feedback into model upgrades

See how to talk to your AI agent using AI Improvement Velocity Tracker.

Give me a high-level overview of our current AI improvement performance.

The current velocity score is 85, with a model improvement rate of 12% and an increasing satisfaction trend.

How efficient are we at turning feedback into model upgrades if we collected 100 entries and implemented 75 with a quality score of 0.8?

The implementation rate is 75% and the efficiency index is 0.6.

What is the impact of a 4-week delay if the improvement rate is 5%?

The calculated velocity score is 42, with a latency impact of 18.

The velocity score is a composite metric that reflects the interplay between implementation speed and the quality of the feedback addressed using `analyze_improvement_latency` and `calculate_feedback_efficiency` logic.

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