Connect Qualra to your AI assistant
Let Cursor, Claude, or any AI tool run user research for you. Hook Qualra up as an MCP server — set up studies, interview customers, and sync insights to your backlog all from a single prompt.
How this works
Overview
Qualra exposes an open-standard Model Context Protocol (MCP) server. Once connected, your local AI assistant can create studies, list surveys, and retrieve raw research insights directly from your terminal or editor workspace.
Step 1
Get your API key
You need a secure API token to authenticate external AI agents with your Qualra workspace. You can generate and manage keys directly from your Dashboard → Settings → API tab.
Authorization Header Format
When issuing manual JSON payloads or cURL handshakes, inject this key-value header:
"Authorization": "Bearer res_api_your_token_here"⚠️ Format Warning
Do not wrap your API key in brackets, curly braces, or template literals (e.g. ${token}). The server expects the raw, un-enclosed token.
Step 2: Choose your setup path
Pick your preferred client or environment — setup takes under 60 seconds.
Claude Desktop
EasiestConfigure custom integrations directly inside the Claude Desktop settings panel.
- 1Open Claude Desktop → Settings → Connectors
- 2Click Add custom connector
- 3Paste the server URL:
https://getqualra.vercel.app/api/mcp - 4Enter your API key when prompted — Claude stores it securely
- 5Done. Try asking: "What surveys are active in my Qualra workspace?"
Developer fallback
If you prefer editing claude_desktop_config.json directly (located at %AppData%\Claude\ on Windows, ~/Library/Application Support/Claude/ on macOS):
claude_desktop_config.json[json]
{
"mcpServers": {
"qualra": {
"type": "sse",
"url": "https://getqualra.vercel.app/api/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_KEY"
}
}
}
}Cursor
For DevsCursor features a built-in MCP manager in the settings panel.
- 1Open Cursor Settings (gear icon or
Ctrl/Cmd + Shift + P→ "Cursor Settings") - 2Navigate to the Features → MCP tab
- 3Click + Add New MCP Server
- 4Set Name to
qualra, Type toSSE, and paste the URL below - 5Hit Save — wait for the green status light
Server Connection URL
https://getqualra.vercel.app/api/mcp?apiKey=YOUR_API_KEYCoding Agents
CustomSelect your AI agent extension environment below to view customized JSON parameters.
Antigravity and Cline share standard MCP configurations. Open your agent's MCP settings file:
Paste this remote SSE config block under your mcpServers key:
cline_mcp_settings.json[json]
{
"mcpServers": {
"qualra": {
"type": "sse",
"url": "https://getqualra.vercel.app/api/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_KEY"
}
}
}
}cURL connection check
For developersExecute a secure RPC handshake check directly from your terminal to verify that the remote server is active and responding:
Test handshake[bash]
curl -X POST https://getqualra.vercel.app/api/mcp \
-H "Content-Type: application/json" \
-H "Accept: application/json, text/event-stream" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{}}'Step 3
Ask your AI assistant
Once successfully connected, test out the integration by prompting your AI assistant with the following scenarios:
Check active surveys
"What surveys are currently active in my Qualra workspace?"
Launch new study
"Draft a checkout friction study for Nairobi users and set it live."
Synthesize insights
"What are the top pain points from my last Qualra study?"
Need help connecting?
Read the official Model Context Protocol remote specs or reach out to our team.