# Dovetail MCP

> Dovetail MCP connects your user research data directly to your AI agent. It lets you manage entire cycles of product discovery—from listing projects and retrieving notes to publishing structured insights—all through natural conversation.

## Overview
- **Category:** productivity
- **Price:** Free
- **Tags:** dovetail, user-research, insights-management, notes-api, ux-research, research-automation, interviews-tracking, mcp

## Description

Stop spending hours manually scrubbing interview transcripts or navigating complex project folders just to find a single piece of feedback. This MCP connects your Dovetail account, giving your AI agent full control over your entire user research lifecycle.

Your agent acts like a dedicated coordinator for your product insights. Need to know what pain points were raised in the 'Mobile UX Redesign' study? Your agent finds them across multiple notes and can even draft an official insight record instantly. You can ask it to list all active projects, then pull up every piece of raw data related to a specific user complaint. If your team needs visibility into who owns which project or what goals were set for the quarter, this MCP handles that retrieval. Because Vinkius hosts this connection, you send one API key and get access to these advanced research workflows right from any compatible AI client.

## Tools

### create_insight
Drafts and publishes a new, structured summary of key research findings.

### create_note
Generates and organizes a brand-new raw data record, such as an interview transcript or usability test log.

### get_project_details
Retrieves detailed metadata about a specific research project's goals and participants.

### list_insights
Lists all existing published research insights to give an overview of findings.

### list_notes
Provides a list of available raw research notes, helping you track where data lives.

### list_projects
Generates a directory listing of every active research project in the workspace.

### list_workspace_members
Retrieves a full list and directory of all people who belong to the research workspace.

## Prompt Examples

**Prompt:** 
```
List all my research projects in Dovetail.
```

**Response:** 
```
I've retrieved your research projects. You have 3 active studies, including 'Mobile UX Redesign' (ID: proj_123) and 'Q4 User Feedback'. Which one would you like to inspect for notes?
```

**Prompt:** 
```
Create a new research note 'User A Interview' in project 'proj_123'.
```

**Response:** 
```
Note created! 'User A Interview' is now added to the Mobile UX project (ID: proj_123). I've set the content type to HTML. Shall I add some initial highlights to this note?
```

**Prompt:** 
```
Show me all published insights containing the word 'mobile'.
```

**Response:** 
```
Searching insights... I've found 2 published findings related to 'mobile'. The most relevant is 'Mobile-first navigation trends' from the latest study. Would you like the full summary for this insight?
```

## Capabilities

### Project Oversight
List all active research projects and retrieve specific goals or metadata for any study.

### Data Capture and Organization
Create new, structured research notes containing raw data like interview transcripts or usability test summaries.

### Insight Publishing
Automatically draft and publish official research findings and key themes that maintain a high-fidelity record of discoveries.

### Advanced Data Retrieval
Search across all projects to find relevant data using powerful filters on titles or content.

### Team Management
Get a complete list of users working within your research workspace, helping coordinate tasks and access rights.

## Use Cases

### Consolidating Q3 Learnings
The PM needs to present the key learnings from three separate studies. They tell their agent: 'List all projects and then find all published insights related to onboarding.' The agent uses `list_projects` and `list_insights`, gathering a comprehensive, actionable report in minutes.

### Onboarding New Team Members
A new Design Lead needs to know who was involved in the initial research phase. They ask their agent to use `list_workspace_members` to get a directory of key contacts, instantly coordinating collaboration and access.

### Logging a Quick Follow-up
The researcher just finished a quick usability test and needs to log it. They tell their agent: 'Create a new note titled 'Follow Up - User C' in the UX project.' The agent uses `create_note` immediately, logging the raw data before they forget the details.

### Project Status Check
The Product Manager needs to know if a study has enough context. They ask their agent to use `get_project_details` for 'Mobile UX Redesign' to confirm its stated goals and participant scope before starting new work.

## Benefits

- Turn raw data into published findings instantly. When you use `create_insight`, your agent drafts a high-fidelity summary of discoveries, keeping the team's knowledge base accurate.
- Never lose context again. Use `list_projects` and then `get_project_details` to quickly understand project goals or participant lists without clicking through multiple tabs.
- Capture everything immediately. When you need to record a new interview or test session, simply ask your agent to execute `create_note`, specifying the content type (HTML or Markdown).
- Find needles in haystacks fast. Use advanced queries to search across projects and notes, dramatically reducing the time needed to locate specific user pain points.
- Keep team communication organized. Running a simple query for `list_workspace_members` ensures everyone knows who they need to talk to about project progress.

## How It Works

The bottom line is that your agent treats Dovetail like a built-in source of truth for all qualitative research data.

1. Subscribe to this MCP on Vinkius and retrieve your Personal API Key from Dovetail settings.
2. Provide the key to your AI agent or client (like Cursor or Claude).
3. Tell your agent what you need—for example, 'List all projects related to user authentication'—and it executes the commands.

## Frequently Asked Questions

**Can I use Dovetail MCP to list all my projects?**
Yes, you can use the `list_projects` tool to retrieve a comprehensive directory of every active study in your workspace. This is useful for getting an overall inventory before starting any deep dive.

**How do I create research notes using Dovetail MCP?**
You use the `create_note` tool, specifying the content type (like HTML or Markdown) and the required data. Your agent will generate a structured record that immediately belongs to your project.

**Is Dovetail MCP just for reading data?**
No, it's fully bi-directional. You can read using tools like `list_insights`, but you can also write and manage data by calling `create_insight` or `create_note`.

**What if I need to know who is on my team for Dovetail MCP?**
The `list_workspace_members` tool lets your agent retrieve a complete directory of everyone in the workspace. This helps you coordinate tasks and manage access permissions.

**Does Dovetail MCP help me find specific user pain points?**
Yes, you can use powerful search queries against projects and notes to pinpoint relevant data across multiple studies. The agent makes this deep search easy to initiate with a simple prompt.