> For the complete documentation index, see [llms.txt](https://docs.coupler.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.coupler.io/destinations/categories/ai/cursor/faq.md).
# FAQ
What is MCP and why does the Cursor integration use it?
MCP stands for Model Context Protocol — an open standard that lets AI applications like Cursor communicate with external data providers in a structured way. Instead of copy-pasting data into a chat window, the MCP connector gives Cursor's AI direct, secure access to your Coupler.io data flows. You get richer, more accurate answers because the AI can query the actual dataset rather than working from a snapshot you manually pasted.
Do I need to know how to code to use Coupler.io with Cursor?
No. The whole point of this integration is to replace code with conversation. Once your data flow is running and the MCP connector is set up, you interact with your data by typing plain-language questions in the Cursor's AI Pane. Cursor is a code editor, but you don't need to write any code to analyze data this way.
Can I send data from multiple sources into Cursor?
Yes. A single Coupler.io data flow can include multiple sources — for example, combining HubSpot deals with Google Sheets revenue data. You can use Join or Append transformations to shape the combined dataset before it reaches Cursor. This means you can ask Cursor questions that span multiple systems without switching between tools.
What kinds of questions can I ask Cursor about my data?
You can ask Cursor to summarize, filter, compare, spot trends, or flag anomalies in your dataset. For example: "which marketing channel drove the most signups last quarter?", "are there any rows where revenue is missing?", or "show me the top 10 customers by order value". The more clearly labeled your data is, the more precise the answers will be.
How do I keep my data fresh in Cursor?
After your first successful manual run, set up a schedule in Coupler.io. Each scheduled run refreshes the data that Cursor can access through the MCP connector. Choose a frequency that matches how often your source data changes — hourly for live dashboards, daily for most reporting use cases.
Every time you start a new chat about your data, Cursor fetches the fresh portion of it. If you want to get updated data in the ongoing conversation, ask Cursor to get it.
Is my data stored inside Cursor?
No. Cursor accesses your data through the Coupler.io MCP connector at query time — the data itself lives in Coupler.io, not inside the Cursor application. This means your data governance policies and Coupler.io access controls still apply.
---
# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.
## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.
Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:
```
GET https://docs.coupler.io/destinations/categories/ai/cursor/faq.md?ask=&goal=
```
`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.
Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.