> For the complete documentation index, see [llms.txt](https://help.dscout.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.dscout.com/dscout-ai/dscout-mcp.md).

# Dscout MCP

{% hint style="info" %}
**Note:** The Dscout MCP is currently in closed beta, meaning only certain users have access and the feature will undergo changes prior to general availability. For more information, contact your Dscout Account Director.
{% endhint %}

The Dscout MCP unlocks your study data and lets your favorite AI tools use it as real-time context, bringing your research projects in-line with your AI workflows. Say goodbye to copying responses and pasting them into Claude for help with analysis. Gone are the days of building prototypes in one tool and designing research around them in another. With the Dscout MCP, you can do it all in the tools you're already using.

### Use cases

Some key use cases for the Dscout MCP include:

* **Study building and management:** Work with the Dscout MCP to design and build a Dscout study that meets your research goals. Define your recruitment criteria, provide any prototypes or concepts you want to test, and draft a launch-ready study right in your AI workflow.
* **Mission recaps and summaries:** Need a quick rundown of the results from a recent study you ran? With the Dscout MCP, you can get a high-level summary of key takeaways or action items based on real participant responses.
* **Artifact creation:** Want to turn your study results into shareable PDFs or visuals? The Dscout MCP can help by leveraging the asset-creation capabilities of your favorite AI tools.
* **Cross-mission analysis:** The Dscout MCP can help you compare responses from multiple Dscout studies at once. Simply tell the MCP which studies you want to analyze, then start asking questions.

### Limitations

The Dscout MCP can do a lot but currently has a few limitations. The Dscout MCP cannot:

* Include piped responses in study questions.
* Recruit from Partner Panels or Private Panels.
* Include rich-text formatting in question prompts, study overviews, etc.
* Build media surveys, AI moderated studies, intercept studies, diary studies, or interview studies.

### Learn more

Ready to get started? Check out the articles below for more information:

<table data-view="cards"><thead><tr><th></th></tr></thead><tbody><tr><td>Set up the Dscout MCP</td></tr><tr><td>MCP tool breakdown</td></tr><tr><td>Best practices</td></tr><tr><td>Troubleshooting</td></tr></tbody></table>


---

# 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://help.dscout.com/dscout-ai/dscout-mcp.md?ask=<question>&goal=<endgoal>
```

`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.