
Connect AI Power User Analytics Engine to ChatGPT and Claude
Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Understand which users drive real platform value.
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.
Your AI does the work. We keep it safe and sound.
No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.
Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

Each Connector runs inside its own sealed environment.
Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.
One switch stops every agent. Instantly.
One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.
Spending limits that pause instead of surprise.
Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.
Three controls, built into the layer your AI connects through.
Curated set · 4 capabilities
We ship only the actions that matter.
01-04
4 capabilities in this set.
Part of 4 available through AI Power User Analytics.
- 01
Analyze feature depth
Evaluates how deeply users are integrating AI into their workflows
- 02
Get power user density
Determines what portion of the user base qualifies as power users
- 03
Predict conversion rate
Estimates the likelihood of standard users becoming power users based on their current trajectory
- 04
Calculate value multiplier
Quantifies the relative importance of power users to the platform's overall utility
Real work
What teams actually run
Launching a New AI Feature
A product team launches a new AI module. They use this MCP to track if the feature is only being used in isolation or if it's integrated into existing, complex workflows.
Identifying High-Value Users
You need to know which 10% of your user base drives 80% of the value. This MCP calculates the value multiplier to pinpoint those critical accounts.
Evaluating Onboarding Success
After a major product update, you run the density capability to see if the new onboarding flow successfully converted a higher percentage of standard users into power users.
Budgeting for Expansion
You forecast user growth by running the conversion rate prediction, allowing you to budget for increased support or infrastructure needs.
One connector, every AI
AI Power User Analytics works with the most popular AI clients.
These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.
Claude
ChatGPT
Gemini
Perplexity
Grok
Microsoft Copilot
Cursor
VS Code
Windsurf
JetBrains
Cline
LangChain
Vercel AI SDK
Lovable
Z.ai
Raycast
Qwen Code
Kimi Code
Le ChatBuilding your own app? The connector is yours to use.
You don't need a client to put AI Power User Analytics to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.
Observed, not estimated
819ms average. Fast in production.
AI Power User Analytics is checked daily against the live service.
- Fastest day
- 588ms
- Slowest day
- 1001ms
- 14-day trend
- Slowing+70%
Connect your client
One URL. Every client.
Activate the Connector, copy your link, and paste it into the client you already use. 4 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 AI Power User Analytics, so you can see the experience inside your AI.
It does not authenticate your account with AI Power User Analytics. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.
AI Power User Analytics Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_OH2xULWGRTCoZ8ovAs5ltjWdJq4c4QqgfPrRRJKW/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 — AI Power User Analytics capabilities are ready to use.
{
"mcpServers": {
"ai-power-user-analytics-engine-mcp": {
"url": "https://edge.vinkius.com/vk_preview_OH2xULWGRTCoZ8ovAs5ltjWdJq4c4QqgfPrRRJKW/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
Guided setup for Claude? Set up AI Power User Analytics in Claude and other AIs
Who it's for
Built for the work AI Power User Analytics owners hand off.
This MCP is essential for product managers and data analysts who need to prove the ROI of AI features. If you're trying to move users from simple trial usage to complex, multi-step workflows, this capability gives you the metrics to back up your strategy.
- 01
Product Manager
Use this MCP to determine if your AI features are being adopted deeply enough to justify the development cost.
- 02
Data Analyst
Run cohort analyses to track how user segment health changes over time and identify key growth bottlenecks.
- 03
Growth Lead
Model user conversion rates to set realistic goals for moving standard users into high-value power user tiers.
FAQ
Questions AI Power User Analytics owners ask.
- 01
What is 'power user density' in this context?
It's a metric that tells you what percentage of your total user base meets the criteria for a 'power user.' It helps you quickly gauge the overall health and maturity of your user base.
- 02
Can this MCP tell me if my AI features are valuable?
Yes. By calculating the value multiplier, you quantify the relative importance of your advanced users. This shows how much value the power users bring compared to the standard user base.
- 03
Do I need to know my user count beforehand?
No. The capabilities are designed to take specific inputs, like the number of power users and standard users, or a list of user counts, to generate the required metrics.
- 04
Is this only for B2B SaaS platforms?
While designed for SaaS, the core metrics—density, value, and feature depth—apply to any platform where user adoption and feature usage need to be quantified.
- 05
What metrics can I calculate?
You can calculate power user density, the value multiplier between user segments, feature depth distribution, and predicted conversion rates.
- 06
How is power user density determined?
By using get_power_user_density, the capability calculates the ratio of users meeting your specified weekly usage threshold against the total user population.
- 07
Can I predict future power users?
Yes, predict_conversion_rate estimates the likelihood of standard users becoming power users based on their current expertise growth trajectory.
Explore
More in Analytics
AI Feature Discovery Analytics AI Connector
Measure and optimize how users find and engage with your AI features.
ViewProduct Usage & Engagement Engine AI Connector
Analyze product stickiness, engagement scores, and user retention correlations.
ViewAI Feature Adoption Analytics AI Connector
Calculate AI feature adoption rates, velocity, stickiness, and funnel efficiency.
ViewAI SaaS Token Economics Engine AI Connector
Analyze token consumption, feature efficiency, and tier-based costs for AI SaaS platforms.
View
Suggestions
UserStack User-Agent Lookup AI Connector
Universal User-Agent intelligence — detect devices, browsers, and OS via AI.
ViewChameleon.io AI Connector
Manage product adoption and onboarding via Chameleon — trigger tours, analyze surveys, and track user events d
ViewAI SaaS Unit Economics Engine AI Connector
Calculate LTV, LTV:CAC, and AI cost impact for AI-driven SaaS models.
ViewAI Output Quality Metrics Engine AI Connector
Quantifies AI performance using feedback, regeneration rates, and acceptance metrics.
View
Connect AI Power User Analytics to Claude, Cursor, ChatGPT & more
