MCP For Claude Marketplace
Accelerator Acceptance Analytics

Accelerator Acceptance Analytics MCP Connector for Claude

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Calculate acceptance probabilities and cohort composition for accelerator programs.

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

This MCP server provides a specialized analytics engine for accelerator program managers. It calculates the probability of application acceptance by factoring in capacity constraints, quality distributions, and strategic referral weighting. Use get_acceptance_metrics to determine overall acceptance rates and effective capacity, analyze_competitive_positioning to evaluate how specific quality tiers perform against the pool, and evaluate_diversity_alignment to ensure the cohort meets specific demographic or sector-based representation goals.

acceleratoranalyticsprobabilitycohortdiversity

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

analyze_competitive_positioning

Provide the target tier name. Determines how a specific applicant's tier affects their chance of success

evaluate_diversity_alignment

Provide the full JSON string for diversity targets. Assesses whether the current applicant pool and capacity allow for meeting specific cohort diversity targets

get_acceptance_metrics

Provide all four required metrics. Calculates the primary acceptance statistics and the impact of referral weighting

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

What is the expected acceptance rate for 100 applications with 10 spots available and 20% referrals?

The expected acceptance rate is 8.5% with an effective capacity adjustment for referrals.

How likely is a 'High-Priority' applicant to be accepted if there are 50 applicants and 5 spots?

An applicant in the High-Priority tier has a 75% probability of acceptance given the current distribution.

Will we meet our 20% female founder target with the current pool?

The current alignment score is 0.85, indicating a high probability of meeting the target, with a gap of only 2% remaining.

The referral multiplier increases the priority of referred applicants, which effectively reduces the remaining spots available for non-referred applicants when using `get_acceptance_metrics`.

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