MCP For Claude Marketplace
Accelerator Cohort Diversity Analytics

Accelerator Cohort Diversity Analytics MCP Connector for Claude

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Analyze cohort diversity, inclusion indices, and performance correlations.

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

This MCP server provides deep analytical insights into startup accelerator cohorts. It allows users to calculate a holistic diversity score, measure the inclusion index against target benchmarks, and identify selection or outreach bias. By using tools like calculate_diversity_metrics, analyze_selection_bias, and evaluate_performance_correlation, accelerators can quantify the relationship between demographic variety and cohort success metrics.

diversityinclusionanalyticsacceleratormetrics

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

analyze_selection_bias

Provide demographic breakdown of all applicants (JSON string) and selected founders (JSON string). Analyzes selection and outreach bias

evaluate_performance_correlation

Provide a list of diversity scores (number) and performance outcomes (number). Evaluates correlation between diversity and performance

calculate_diversity_metrics

Provide demographic counts for gender, race, and geography (JSON string). Calculates diversity, inclusion, and cohort composition metrics

See how to talk to your AI agent using Accelerator Cohort Diversity Analytics.

Calculate the diversity metrics for a cohort with these demographics: { "gender": {"m": 10, "f": 10}, "raceEthnicity": {"groupA": 10, "groupB": 10}, "geography": {"us": 15, "intl": 5} }, industries: ["SaaS", "FinTech"], and education: ["University"]

The cohort has a diversity score of 0.85 and an inclusion index of 0.92, reflecting a highly balanced composition across gender and ethnicity.

Analyze the bias between an applicant pool of { "groupA": 50, "groupB": 50 } and a selected cohort of { "groupA": 40, "groupB": 10 }.

The analysis indicates a high selection bias score, suggesting the selection process is favoring groupA over groupB.

Is there a correlation between these diversity scores [0.5, 0.7, 0.9] and these performance metrics [1M, 2M, 5M]?

There is a strong positive correlation (0.98) between diversity scores and performance outcomes, which is statistically significant.

The `calculate_diversity_metrics` tool aggregates variety across gender, race/ethnicity, and geography to produce a holistic score.

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