Does this MCP analyze real-time data?

The MCP processes data to calculate impact and signals. It provides the mathematical framework for measurement, helping you understand the relationship between feature usage and your North Star Metric.

What is the difference between NSM contribution and predictive strength?

NSM contribution calculates the percentage of the metric movement tied to a feature. Predictive strength assesses how reliable a metric is as a signal for future growth.

Can I use this to decide what to build next?

Yes. The MCP provides a final priority ranking that combines both mathematical impact and strategic alignment, helping you make data-backed decisions for your roadmap.

Is this capability only for AI features?

While it is designed for AI features, the underlying framework measures the relationship between any feature usage and your core product goals.

How is the AI contribution calculated?

The contribution is determined by the product of the feature usage volume and its correlation strength, normalized against the total NSM value using the get_nsm_contribution capability.

Can I use this to prioritize my product roadmap?

Yes. By using rank_feature_priority, you can combine NSM contribution, indicator strength, and strategic alignment to generate a prioritized list of AI features.

What are leading indicators in this context?

Leading indicators are predictive metrics that move before the NSM. You can use evaluate_leading_indicator to determine how reliably these signals predict future North Star Metric changes.

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Connect AI Feature Nsm 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. Move product decisions from gut feeling to precise data.

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 NSM Analyzer.

01
Rank feature priority
Generates a final priority ranking for an AI feature by combining mathematical impact with strategic intent
02
Evaluate leading indicator
Determines how predictive a specific leading indicator is for the North Star Metric
03
Get feature impact summary
Provides a high-level overview of a feature's health and contribution status
04
Get nsm contribution
Calculates the specific percentage of the North Star Metric that is driven by a specific AI feature

Real work

What teams actually run

Feature Comparison

You want to know if Feature A or Feature B is more valuable. Run a comparison to see which one has a higher NSM contribution percentage.

Roadmap Planning

The team needs to decide what to build next. Use the ranking capability to get a prioritized list combining impact and strategy.

Metric Validation

You suspect a metric might be misleading. Use the leading indicator capability to check its predictive strength for the NSM.

Quarterly Review

You need to report on product success. Get a high-level summary of feature health to show stakeholders where the product is succeeding.

One connector, every AI

NSM 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 NSM 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

896ms average. Fast in production.

NSM Analyzer is checked daily against the live service.

Daily averagePeak 1019ms

Oct 3Today

Fastest day: 686ms
Slowest day: 1019ms
14-day trend: Slowing+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 NSM Analyzer, so you can see the experience inside your AI.

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

NSM Analyzer Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_yFt3TdlAk1TjCAGDiKY3X5VrqTckG0etrUBdM4oM/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 — NSM Analyzer capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "ai-feature-nsm-analyzer-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_yFt3TdlAk1TjCAGDiKY3X5VrqTckG0etrUBdM4oM/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 NSM Analyzer in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work NSM Analyzer owners hand off.

Product Managers and Product Owners use this MCP to stop making product decisions based on gut feelings. It provides a data-driven way to prove which AI features are actually moving the needle on your company's most important metric.

01
Product Manager
Use this to justify roadmap changes and prove the ROI of new features.
02
Product Owner
Use this to align feature development with the measurable goals of the business.
03
Data Analyst
Use this to model the complex relationship between feature usage and core business metrics.

FAQ

Questions NSM Analyzer owners ask.

01
Does this MCP analyze real-time data?
The MCP processes data to calculate impact and signals. It provides the mathematical framework for measurement, helping you understand the relationship between feature usage and your North Star Metric.
02
What is the difference between NSM contribution and predictive strength?
NSM contribution calculates the percentage of the metric movement tied to a feature. Predictive strength assesses how reliable a metric is as a signal for future growth.
03
Can I use this to decide what to build next?
Yes. The MCP provides a final priority ranking that combines both mathematical impact and strategic alignment, helping you make data-backed decisions for your roadmap.
04
Is this capability only for AI features?
While it is designed for AI features, the underlying framework measures the relationship between any feature usage and your core product goals.
05
How is the AI contribution calculated?
The contribution is determined by the product of the feature usage volume and its correlation strength, normalized against the total NSM value using the get_nsm_contribution capability.
06
Can I use this to prioritize my product roadmap?
Yes. By using rank_feature_priority, you can combine NSM contribution, indicator strength, and strategic alignment to generate a prioritized list of AI features.
07
What are leading indicators in this context?
Leading indicators are predictive metrics that move before the NSM. You can use evaluate_leading_indicator to determine how reliably these signals predict future North Star Metric changes.

Explore

More in Product Management

Connect NSM 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

Rank feature priority

Evaluate leading indicator

Get feature impact summary

Get nsm contribution

What teams actually run

Feature Comparison

Roadmap Planning

Metric Validation

Quarterly Review

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

NSM Analyzer Connector

Claude Desktop

Product Manager

Product Owner

Data Analyst

Does this MCP analyze real-time data?

What is the difference between NSM contribution and predictive strength?

Can I use this to decide what to build next?

Is this capability only for AI features?

How is the AI contribution calculated?

Can I use this to prioritize my product roadmap?

What are leading indicators in this context?

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