How to Use the CustomerGauge MCP in Cursor

Q: How do I connect CustomerGauge to my Cursor workspace?

Create an mcp.json file in your project root directory. Paste the Vinkius MCP Server URL under the servers list. Turn on Agent mode in the chat panel to activate the tools.

Give Cursor direct access to the CustomerGauge MCP Server to build internal dashboards and reporting scripts with real B2B data.

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Connect CustomerGauge MCP to Cursor

Create your Vinkius account to connect CustomerGauge to Cursor and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup CustomerGauge with Cursor

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Pull live account data directly into Cursor

The `list_b2b_accounts` tool feeds real account IDs and organizational mappings straight into your editor. Instead of writing mock data for a new customer success dashboard, your agent injects the actual production accounts you manage. Fetching the people attached to those businesses happens through `list_account_contacts`. Cursor grabs the contact identifiers so you can test your CRM integration code against real relationship boundaries.

Build feedback loops with this MCP Server

Triggering `list_survey_responses` resolves response IDs, Net Promoter Scores, and timestamp data. When you write a script to aggregate weekly feedback, the AI writes the data processing logic using the exact schema returned by the API. Testing search functionality is just as fast. The `search_responses_by_keyword` tool lets Cursor query the indexed text search boundary, proving your filtering logic works on actual customer comments before you commit the code.

Inject revenue and NPS metrics into your code

Using `get_account_nps` resolves quantitative satisfaction scores for specific clients. You ask the agent to write a function that flags at-risk accounts, and it tests the threshold logic against live sentiment data. Tying that to financial impact requires `list_revenue_impact_data`. The editor pulls monetary values associated with those accounts, letting you build accurate ROI calculation modules without ever leaving your IDE.

Setup guide

Set up CustomerGauge MCP in Cursor

Prerequisites

Cursor installed (macOS, Windows, or Linux)
Active Vinkius subscription with a valid endpoint token

1

Open MCP Settings

Go to Cursor Settings → MCP or open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and search for "MCP: Add Server".
2

Add the CustomerGauge MCP

Cursor will create or open .cursor/mcp.json in your project root. Paste the JSON snippet on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Enable Agent mode

Open Composer (Cmd+I / Ctrl+I) and switch to Agent mode using the dropdown at the top. MCP tools are only available in Agent mode.
4

Verify the connection

Ask Cursor something like "List my recent CustomerGauge transactions." If the MCP tools are loaded correctly, Cursor will call the CustomerGauge tools automatically. You can also check Settings → MCP for a green status indicator.

.cursor/mcp.json

{
  "mcpServers": {
    "customergauge-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by CustomerGauge. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about CustomerGauge MCP in Cursor

Create an `mcp.json` file in your project root directory. Paste the Vinkius MCP Server URL under the servers list. Turn on Agent mode in the chat panel to activate the tools.

The agent writes functions while actively pulling live quantitative satisfaction scores. It uses the real API responses as context instead of guessing the data structure.

It interacts directly with organizational performance data when you request it. You can ask the AI to map out your divisions based on the live API output.

The tools always fetch the current structure from the endpoint. Your agent reads the live response and adapts the code it writes to match the latest data format.

Every request containing monetary values and account associations runs through a managed, zero-trust proxy. Vinkius isolates the execution environment and destroys it immediately after your IDE receives the payload. No financial metrics are stored on the broker.

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