Use Accelerator Attendance Predictor with your AI.
Connect your account once and let the AI you already use work with it, without building another integration. Know exactly how many people to expect.
Developed, maintained, and hosted by Vinkius.
MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED
Waiting for input…
Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.
Complete set · 3 capabilities
The complete Accelerator Attendance Predictor capability set.
These are the exact actions your AI can choose when you ask it to work with Accelerator Attendance Predictor.
01-03
3 capabilities in this set.
Part of 3 available through Accelerator Attendance Predictor.
- 01
Analyze tier distribution
- 02
Predict attendance
- 03
Recommend overbooking strategy
Observed, not estimated
773ms average. Fast in production.
Accelerator Attendance Predictor is checked daily against the live service.
- Fastest day
- 686ms
- Slowest day
- 924ms
- 14-day trend
- Stable-4%
Connect your client
One URL. Every client.
Activate the Connector, copy your link, and paste it into the client you already use. 3 capabilities arrive ready to run.
Preview access · not provider authentication
The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Accelerator Attendance Predictor, so you can see the experience inside your AI.
It does not authenticate your account with Accelerator Attendance Predictor. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.
Accelerator Attendance Predictor Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_VrildaLLy6tNy29HVI0uAY8b7exhXwhCxSXj8N6f/mcpClaude Desktop
Follow the steps below to connect in seconds.
- 1In Claude Desktop, open Settings → Connectors.
- 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
- 3Click Add and start a new chat — Accelerator Attendance Predictor capabilities are ready to use.
{
"mcpServers": {
"accelerator-demo-day-attendance-predictor-mcp": {
"url": "https://edge.vinkius.com/vk_preview_VrildaLLy6tNy29HVI0uAY8b7exhXwhCxSXj8N6f/mcp"
}
}
}
Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline
Step-by-step instructions for each client are in the guide. How to connect
Who it's for
Built for the work Accelerator Attendance Predictor owners hand off.
This MCP is built for people who manage high-stakes, scheduled events. If you plan Demo Days, pitch events, or investor gatherings, this capability gives you the data to plan capacity and mailing lists accurately.
- 01
Accelerator Manager
Use it to forecast attendance and manage the overall event capacity for cohorts.
- 02
Event Planner
Use it to set realistic guest counts and manage venue size requirements.
- 03
Venture Capitalist
Use it to understand the expected composition of the investor crowd.
FAQ
Questions Accelerator Attendance Predictor owners ask.
- 01
What kind of data does this MCP need to run?
It requires historical attendance rates and an assessment of the startup's appeal. The more accurate the historical data you provide, the better the predictions will be.
- 02
Does this predict the exact number of people?
No, it provides a predictive estimate. It uses statistical models to give you a highly probable range, helping you plan for the most likely scenario.
- 03
Can I use this for events other than Demo Days?
The core functionality is event forecasting. As long as your event has historical attendance data and a measurable appeal factor, you can adapt the capability.
- 04
What is the difference between the capabilities?
The predict_attendance gives you the total number. analyze_tier_distribution tells you who those people are. recommend_overbooking_strategy tells you how many invitations to send.
- 05
Is this MCP reliable for major events?
It is built on predictive analytics designed for high-stakes event management. It helps you move from guesswork to data-driven planning.
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