What kind of data does this MCP analyze?

This MCP analyzes user journey data for AI SaaS products. It focuses on the time between a user signing up and their first meaningful interaction with your AI features.

Can I predict the effect of changing my product?

Yes. You can use the simulation capability to predict how reducing path complexity or removing barriers will affect your overall activation rate.

What is 'activation timing' in this context?

Activation timing measures the time it takes a user to reach a key milestone or perform their first core action within your product. It's a key metric for SaaS growth.

Does this MCP only work for large companies?

No. It works for any AI SaaS product. You can use it to analyze the user flow and find friction points regardless of your company size.

What is the difference between getting metrics and analyzing barriers?

Getting metrics gives you the 'what'—like the median activation days. Analyzing barriers tells you the 'why'—identifying the specific friction points causing the slowdown.

How do I calculate the median time to activation?

You can use the get_activation_metrics capability by providing the specific cohortId and onboardingPathId.

Can I predict the impact of simplifying my onboarding flow?

Yes, the simulate_acceleration_strategies capability allows you to model how reducing barriers or simplifying the path affects activation velocity.

How can I identify where users are dropping off?

Use the get_milestone_progress capability to view completion rates and identify specific drop-off points in the user journey.

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Connect AI Feature Activation Analyzer 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. Find exactly where users drop off and how to fix it.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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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.

V8 Isolate01

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.

Kill Switch02

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.

FinOps per User03

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.

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through AI Feature Activation Analyzer.

01
Analyze activation barriers
Identifies which specific friction points are most significantly impacting the activation rate
02
Get activation metrics
Calculates the core timing metrics for a specific user group
03
Get milestone progress
Tracks user movement through the sequence of milestones to find where users drop off
04
Simulate acceleration strategies
Predicts how changes to the onboarding path or reduction in barriers will affect activation velocity

Real work

What teams actually run

Optimizing Onboarding Flows

Your team just launched a new guided flow. Use this MCP to immediately check if the new path reduced the time it takes users to activate.

Debugging Low Retention

If retention suddenly drops, use the barrier analysis capability to pinpoint if the issue is technical (latency) or conceptual (difficulty).

Testing New Features

Before committing resources, simulate how adding a new feature or simplifying a step will change the overall activation velocity.

Segment Performance Review

You need to compare the activation metrics between your 'Enterprise' and 'SMB' user groups to allocate resources better.

One connector, every AI

AI Feature Activation Analyzer 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.

Building your own app? The connector is yours to use.

You don't need a client to put AI Feature Activation Analyzer 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

911ms average. Fast in production.

AI Feature Activation Analyzer is checked daily against the live service.

Daily averagePeak 1014ms

Oct 3Today

Fastest day: 721ms
Slowest day: 1014ms
14-day trend: Improving-11%

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 Feature Activation Analyzer, so you can see the experience inside your AI.

It does not authenticate your account with AI Feature Activation Analyzer. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

AI Feature Activation Analyzer Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_Fx3fkcdhw96O3nIwZxTZvieAVhU0t6VC6a2pVK2O/mcp

Claude 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 Feature Activation Analyzer capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "ai-feature-activation-analyzer-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_Fx3fkcdhw96O3nIwZxTZvieAVhU0t6VC6a2pVK2O/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 Feature Activation Analyzer in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work AI Feature Activation Analyzer owners hand off.

This MCP is built for Product Managers and Growth Leads who need hard data on user behavior. If you're responsible for improving the onboarding funnel or boosting retention, this capability gives you the metrics you need to make changes that actually move the needle.

01
Product Manager
Use it to map the user journey and identify the specific points of friction that slow down feature adoption.
02
Growth Marketer
Run simulations to predict the impact of new marketing flows or onboarding copy changes on activation time.
03
SaaS Founder
Get a clear, data-driven view of user retention and where your product is losing its early adopters.

FAQ

Questions AI Feature Activation Analyzer owners ask.

01
What kind of data does this MCP analyze?
This MCP analyzes user journey data for AI SaaS products. It focuses on the time between a user signing up and their first meaningful interaction with your AI features.
02
Can I predict the effect of changing my product?
Yes. You can use the simulation capability to predict how reducing path complexity or removing barriers will affect your overall activation rate.
03
What is 'activation timing' in this context?
Activation timing measures the time it takes a user to reach a key milestone or perform their first core action within your product. It's a key metric for SaaS growth.
04
Does this MCP only work for large companies?
No. It works for any AI SaaS product. You can use it to analyze the user flow and find friction points regardless of your company size.
05
What is the difference between getting metrics and analyzing barriers?
Getting metrics gives you the 'what'—like the median activation days. Analyzing barriers tells you the 'why'—identifying the specific friction points causing the slowdown.
06
How do I calculate the median time to activation?
You can use the get_activation_metrics capability by providing the specific cohortId and onboardingPathId.
07
Can I predict the impact of simplifying my onboarding flow?
Yes, the simulate_acceleration_strategies capability allows you to model how reducing barriers or simplifying the path affects activation velocity.
08
How can I identify where users are dropping off?
Use the get_milestone_progress capability to view completion rates and identify specific drop-off points in the user journey.

Explore

More in Analytics

Connect AI Feature Activation Analyzer to Claude, Cursor, ChatGPT & more

Your AI does the work. We keep it safe and sound.

Each Connector runs inside its own sealed environment.

One switch stops every agent. Instantly.

Spending limits that pause instead of surprise.

We ship only the actions that matter.

01-04

Analyze activation barriers

Get activation metrics

Get milestone progress

Simulate acceleration strategies

What teams actually run

Optimizing Onboarding Flows

Debugging Low Retention

Testing New Features

Segment Performance Review

Building your own app? The connector is yours to use.

AI Feature Activation Analyzer Connector

Claude Desktop

Product Manager

Growth Marketer

SaaS Founder

What kind of data does this MCP analyze?

Can I predict the effect of changing my product?

What is 'activation timing' in this context?

Does this MCP only work for large companies?

What is the difference between getting metrics and analyzing barriers?

How do I calculate the median time to activation?

Can I predict the impact of simplifying my onboarding flow?

How can I identify where users are dropping off?

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