Accelerator Instructor Effectiveness

Accelerator Instructor Effectiveness MCP Connector for Claude

A+

Calculate instructor performance scores, effectiveness trends, and get curriculum-based instructor recommendations.

3 tools Official Updated Oct 1, 2026 Official Vinkius Partner

This MCP server provides tools to evaluate instructor performance within accelerator programs. It calculates a comprehensive instructor score using attendance, satisfaction, and outcome correlation. You can also analyze performance trajectories with get_effectiveness_trend or find the best matches for upcoming sessions using recommend_instructors based on topic and teaching style.

instructormetricsperformanceacceleratoreducation-analytics

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

recommend_instructors

Suggest the most suitable instructors for a specific upcoming curriculum or session

get_effectiveness_trend

Determine if an instructor's performance is improving, declining, or staying consistent

get_instructor_score

Calculate a single, comprehensive effectiveness score for a specific instructor

See how to talk to your AI agent using Accelerator Instructor Effectiveness.

What is the effectiveness score for instructor ID 'inst_99' with 90% attendance, 8.5 satisfaction, 0.7 correlation, and 50% repeat rate?

The instructor 'inst_99' has a total effectiveness score of 82 and is currently categorized as 'Elite'.

Is the performance of instructor 'inst_42' improving based on these scores: 75, 80, 85?

Yes, the performance for 'inst_42' is showing an 'Upward' trend with a positive momentum score.

Recommend instructors for a 'Product Management' workshop with a 'Coaching' style and a minimum score of 80.

I found 2 instructors matching your criteria: Sarah Jenkins and Michael Chen.

The score is a weighted combination of attendance rate, student satisfaction, outcome correlation, and repeat invitation rates.

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