Integrate Zengain with Claude, Cursor, Chatbots & AI Agents MCP Server

Q: How do I see high-level usage summary for a specific product?

Use the getanalyticssummary tool. You can optionally provide a Product ID to filter the metrics for that specific offering.

Identify high-intent website visitors by company and reach out to warm leads before they fill out a form or contact you.

GDPR Free for Subscribers

Compatible with every major AI agent and IDE

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

+ other MCP clients

get

Get analytics summary on Zengain

Get analytics summary

get

Get health score on Zengain

Get customer health score

get

Get product on Zengain

Get details for a specific product

get

Get user details on Zengain

Get details for a specific user

list

List events on Zengain

List tracking events

list

List kpms on Zengain

List Key Product Milestones

list

List products on Zengain

List Zengain products

list

List users on Zengain

List product users

list

List webhooks on Zengain

List configured webhooks

track

Track event on Zengain

Track a custom event

Security & Code Integrity Audit

Every tool in the Zengain MCP Server is continuously audited by the Vinkius Security Engine. We guarantee zero-trust payload isolation, strict data boundaries, and deterministic execution for enterprise-grade AI agents.

A+Score: 100

How Vinkius protects your data

Can I audit what my AI agents are doing with this integration?

Yes, Vinkius provides an immutable, HMAC-chained audit log. Every tool execution, payload, and response is tracked in real-time on your dashboard, giving you complete visibility into your agent's actions.

How do I see high-level usage summary for a specific product?

Use the get_analytics_summary tool. You can optionally provide a Product ID to filter the metrics for that specific offering.

What happens if the underlying API rate limits my agent?

Our edge infrastructure automatically handles backoffs, queueing, and throttling. If an AI agent sends too many erratic requests, Vinkius manages the rate limits gracefully, ensuring your backend doesn't crash.

What if the AI ends up reading customer data or confidential information?

We have a built-in digital "bodyguard" called DLP (Data Loss Prevention). If a tool fetches data and the response contains social security numbers, credit cards, or personal customer info, Vinkius magically blocks and erases that information before it is delivered to the AI. The AI works only with what is strictly necessary, and your sensitive data never leaks.

Supported Use Cases for Zengain

The Zengain integration provides structured, LLM-friendly schemas for reliable tool execution within your agentic workflows.

Streamlining customer success

The Zengain integration exposes LLM-friendly schemas for customer success. Tools like Cursor can map natural language directly into executable data analytics commands.

Scaling product analytics via MCP

Integrate the Zengain server to handle product analytics requests natively. It provides the schemas required for ChatGPT and Cursor to manage data analytics data.

Zengain. Runs on everything.

From IDE to framework. Every connection governed by Vinkius.

Claude DesktopIDE

Anthropic's native desktop app for Claude with built-in MCP support.

CursorIDE

AI-first code editor with integrated LLM-powered coding assistance.

VS Code CopilotIDE

GitHub Copilot in VS Code with Agent mode and MCP support.

WindsurfIDE

Purpose-built IDE for agentic AI coding workflows.

ClineIDE

Autonomous AI coding agent that runs inside VS Code.

Claude CodeCLI

Anthropic's agentic CLI for terminal-first development.

OpenAI Agents SDKSDK

Python SDK for building production-grade OpenAI agent workflows.

Google ADKSDK

Google's framework for building production AI agents.

Pydantic AISDK

Type-safe agent development for Python with first-class MCP support.

Vercel AI SDKSDK

TypeScript toolkit for building AI-powered web applications.

Mastra AISDK

TypeScript-native agent framework for modern web stacks.

CrewAIFramework

Python framework for orchestrating collaborative AI agent crews.

LangChainFramework

Leading Python framework for composable LLM applications.

LlamaIndexFramework

Data-aware AI agent framework for structured and unstructured sources.

AutoGenFramework

Microsoft's framework for multi-agent collaborative conversations.

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