• PROBABILITY
  • CAPACITY
  • WEIGHTING
  • HUMAN

How to calculate acceptance rates with your AI

Connect your data once. Your AI then handles the heavy lifting of modeling cohort probabilities and capacity limits.

Ask AI about this page

Short answer

How do I calculate acceptance rates with my AI?

Your AI uses specific cohort constraints and referral weights to run statistical models against your current data. You get a breakdown of acceptance probabilities and how much effective capacity you actually have left.

The outcomes

What your analysis produces

Once the data is processed, your AI delivers these specific insights.

PROBABILITY

Acceptance likelihoods

The AI calculates the statistical chance of acceptance for different applicant profiles. You see exactly where your odds sit based on current trends.

CAPACITY

Effective capacity limits

The AI determines how many more applicants you can realistically take. It accounts for your specific cohort constraints to prevent over-enrollment.

WEIGHTING

Referral impact analysis

The AI applies your specific referral weights to the data. This shows how different sources change your overall acceptance math.

HUMAN

Manual oversight needed

The AI provides the numbers, but you decide if the constraints are too tight or too loose. You retain full control over the final policy changes.

The workflow

What your AI does when the data arrives.

The AI moves from raw data to actionable statistical models through these steps.

  1. Data ingestion

    The AI pulls your current cohort data and applies the constraints you've set.

    get_acceptance_metrics

  2. Weight application

    It adjusts the incoming data based on your specific referral weights.

    get_acceptance_metrics

  3. Probability modeling

    The AI runs the math to find the likelihood of acceptance for your specific groups.

    get_acceptance_metrics

  4. Capacity calculation

    It determines your remaining effective capacity so you don't overfill your cohort.

    get_acceptance_metrics

Try it

Copy these to start.

Paste these directly into your chat to begin.

Starting points

These are starting points. Swap out the bracketed info for your actual cohort names or referral sources.

Accelerator Analytics Engine Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_wYJDajtH9GeGtCIGxFdOc9FdE4efRvKvU1vJXL8U/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Accelerator Analytics Engine capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "accelerator-acceptance-analytics-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_wYJDajtH9GeGtCIGxFdOc9FdE4efRvKvU1vJXL8U/mcp"
    }
  }
}
Copy into chat04

  • Calculate the acceptance probability for the Summer 2025 cohort.

  • What is my effective capacity if I add a 20% weight to referral source X?

  • Show me the acceptance metrics for applicants with the current cohort constraints.

  • How much capacity do I have left if I adjust my referral weights for the tech sector?

  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Start here

Connect Accelerator Acceptance Analytics once, then ask.

One connection links your data to your AI client. Your credentials stay encrypted and you can start asking questions immediately.

Connect Accelerator Acceptance Analytics to your AI

FAQ

Common questions

  • 01

    Can the AI change my cohort constraints automatically?

    No. The AI only reads the constraints to perform calculations. You must manually update your constraints in your own system.

  • 02

    Does the AI delete any of my existing referral data?

    No. The AI only has read access to your metrics. It cannot modify, delete, or overwrite your original data.

  • 03

    How does it handle different referral weights?

    The AI applies the weights you provide to the statistical model to show how those weights shift your acceptance probabilities.

  • 04

    Can I use this with any AI client?

    Yes, you can use this with any MCP-compatible client like Claude, Cursor, or Windsurf.

  • 05

    What is 'effective capacity'?

    It is a calculation of how many more people you can accept before hitting your specific cohort limits, based on current trends.

  • More questions about Accelerator Acceptance Analytics? The Connector page answers them. See everything the Accelerator Acceptance Analytics Connector can do

Connect Accelerator Analytics Engine to Claude, Cursor, ChatGPT & more