MCP For Claude Marketplace
Accelerator Mentorship Analytics

Accelerator Mentorship Analytics MCP Connector for Claude

A+

Quantify the impact of mentorship on startup success and optimize engagement intensity.

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

This MCP server provides analytical tools to measure the relationship between mentorship investment and startup outcomes. It allows users to calculate the correlation between mentor hours and success, identify the optimal mentorship intensity to avoid diminishing returns, and determine the ROI of mentorship efforts. By accounting for company quality scores, the tools mitigate self-selection bias, providing a clear view of how mentor quality and time drive results. Use get_correlation_analysis to assess impact, find_optimal_intensity to find the engagement sweet spot, and calculate_mentor_roi to measure efficiency.

mentorshipstartupcorrelationroianalyticsoptimization

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

get_correlation_analysis

Calculates the statistical relationship between mentorship efforts and startup success, adjusted by company quality scores to mitigate self-selection bias

calculate_mentor_roi

Determines the value generated by mentorship relative to the effort invested

find_optimal_intensity

Identifies the most efficient amount of mentorship time to achieve desired outcomes

See how to talk to your AI agent using Accelerator Mentorship Analytics.

Calculate the correlation between mentorship and success for my cohort.

The correlation coefficient for your cohort is 0.72, with an adjusted strength of 0.65 after accounting for company quality scores.

What is the most efficient amount of hours to spend with startups?

The optimal mentorship intensity is 12 hours per company, with a recommended range of 10 to 15 hours to maintain high efficiency.

What is the ROI for the recent mentorship cycle?

The mentor ROI is 4.5, indicating high efficiency in converting mentor time and quality into startup success.

The `get_correlation_analysis` tool uses company quality scores to adjust the correlation coefficient, ensuring that the impact of mentorship is not overstated due to high-quality startups naturally succeeding.

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