> ## Documentation Index
> Fetch the complete documentation index at: https://docs.humanize.app/llms.txt
> Use this file to discover all available pages before exploring further.

# Humanize MCP

> Connect Claude, ChatGPT, Cursor, and other AI tools directly to your research.

The Humanize MCP server lets AI assistants read your research. Connect it once, then ask questions in the tool you already work in — no exporting, no copy-paste, no switching to the dashboard.

**Server URL**

```
https://go.humanize.app/api/mcp
```

<Card title="Connect your client" icon="plug" href="/mcp/connect">
  Setup for Claude, ChatGPT, Cursor, Codex, and VS Code — takes about a minute.
</Card>

## What you can do

Once connected, your assistant can reach everything the dashboard shows for a study, minus participant identities.

| You ask                                                                | It uses                     |
| ---------------------------------------------------------------------- | --------------------------- |
| "What studies have we run this year?"                                  | `list_studies`              |
| "Summarize the findings from the onboarding study"                     | `get_study_summary`         |
| "Which themes came up most, and how many participants mentioned each?" | `list_themes`, `get_theme`  |
| "Pull the quotes about pricing objections"                             | `get_theme`, `search`       |
| "How did participants answer question 4?"                              | `get_question_breakdown`    |
| "What archetypes did we find?"                                         | `get_personas`              |
| "Compare what participants said about delivery times"                  | `get_participant_responses` |
| "How did the screener population break down?"                          | `get_screener_results`      |
| "Did anyone mention our competitor by name?"                           | `search`, `fetch`           |
| "Why did lapsed users churn, based on the transcripts?"                | `ask_study`                 |

Because your assistant can call several tools in one turn, the useful questions are the ones that cut across studies: *"We ran three studies on checkout — what did all of them agree on?"* Answering that by hand means opening three reports. Here it's one prompt.

<Note>
  **The connection is read-only.** Every tool reads; none of them create, edit, launch, or delete anything. An assistant cannot change your studies, publish a session, or touch participant data. The worst it can do is read something and get it wrong — which is why answers are worth spot-checking against the dashboard.
</Note>

## What you need

* A Humanize account that belongs to a workspace
* An MCP client that supports remote servers with OAuth — Claude, ChatGPT, Cursor, Codex, and VS Code all qualify

You don't need an API key. Authentication runs through the same sign-in you use for the dashboard.

## How access works

When you connect, you sign in and pick one workspace. The connection is scoped to you and that workspace:

* Your assistant sees exactly the studies you'd see in the dashboard, and nothing outside the workspace you selected.
* To reach a second workspace, connect again and select it during sign-in.
* Removing the connector from your client ends its access.

## Good to know

* **Findings need a completed analysis.** A study that hasn't finished analysis returns metadata and screener results, but no themes, personas, or summary. `list_studies` reports `hasAnalysis` for each study, so your assistant can check first.
* **Results reflect the latest analysis.** If you re-run analysis, the tools return the new version.
* **Participants are anonymized.** Quotes are attributed like "Lapsed user, 38" or "Participant #12" — never a real name or email. See [Data and limits](/mcp/data-and-limits).