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Connect Customer Rating Analytics 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. Turn raw star ratings into clear statistical insights.

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.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

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.

A futuristic MCP client docking bay
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 Customer Rating Analytics.

  1. 01

    Calculate rating metrics

    This capability computes the average, total count, and a rounded display rating from a provided list of star ratings.

  2. 02

    Get rating distribution

    This capability identifies the frequency of each star level within a dataset to show how ratings are spread out.

  3. 03

    Get rating summary by range

    This capability counts how many ratings fall within specific satisfaction tiers or numerical ranges.

  4. 04

    Validate rating input

    This capability checks if a single rating value is valid according to standard rating rules.

Real work

What teams actually run

01

Sentiment Trend Analysis

Your agent compares the distribution of ratings between two different time periods.

02

Satisfaction Tiering

You count how many customers fall into the 4 to 5 star range to measure high satisfaction.

03

Data Cleaning

The capability validates rating inputs to catch errors in your feedback datasets.

04

Quick Reporting

Get a rounded display rating and total count for a quick summary of a product's performance.

One connector, every AI

Customer Rating 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.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

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

You don't need a client to put Customer Rating 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

803ms average. Fast in production.

Customer Rating Analytics is checked daily against the live service.

Daily averagePeak 945ms
Oct 9Today
Fastest day
723ms
Slowest day
945ms
14-day trend
Slowing+24%

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 Customer Rating Analytics, so you can see the experience inside your AI.

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

Customer Rating Analytics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_2xQ0dlr1P6PRlWhg3DjwX0jlsuW01ef2PzDUizc9/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 — Customer Rating Analytics capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "customer-rating-analytics-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_2xQ0dlr1P6PRlWhg3DjwX0jlsuW01ef2PzDUizc9/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 Customer Rating Analytics in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Customer Rating Analytics owners hand off.

This MCP is built for anyone managing customer feedback loops who needs quick math on rating datasets.

  • 01

    Product Managers

    Hand raw feedback exports to your agent to quickly gauge feature satisfaction.

  • 02

    Customer Success Leads

    Use the capability to monitor shifts in customer sentiment through rating distributions.

  • 03

    Data Analysts

    Offload basic statistical aggregation of star ratings to your AI client.

FAQ

Questions Customer Rating Analytics owners ask.

  • 01

    What can this MCP do with my star ratings?

    It calculates averages, counts total ratings, shows how many people gave each star level, and groups ratings into specific ranges.

  • 02

    Which AI clients can use this MCP?

    You can use this with any MCP-compatible client, including Claude, Cursor, Windsurf, and VS Code.

  • 03

    Do I need to host this myself?

    No, Vinkius hosts and manages the MCP for you. You just connect it to your client and it is ready to use.

  • 04

    Can I use it to check if a rating is valid?

    Yes, the validate_rating_input capability is specifically designed to verify if a single rating is valid.

  • 05

    How does it handle satisfaction tiers?

    The get_rating_summary_by_range capability allows your agent to count how many ratings fall within specific numerical ranges you define.

  • 06

    What kind of data can I analyze?

    You can analyze arrays of integer star ratings ranging from 1 to 5 using calculate_rating_metrics and other specialized capabilities.

  • 07

    How do I check if a rating is valid?

    Use the validate_rating_input capability to confirm if a specific integer falls within the required 1 to 5 star range.

  • 08

    Can I see how many people gave 5 stars?

    Yes, use get_rating_distribution to receive an object showing the count for every star level from 1 to 5.

Explore

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