Claude Integration
Introduction
Section titled “Introduction”This guide explains how to connect Refiner to Claude so you can analyze survey response data directly within your conversations. Once connected, you can leverage Claude’s natural language capabilities to summarize open-ended responses, detect trends, extract themes, and generate actionable insights from your survey data.
By integrating Refiner via its MCP (Model Context Protocol) server, you enable Claude to securely access and process your survey data. This allows you to:
- Summarize qualitative (open-text) responses
- Identify recurring themes and sentiment
- Segment feedback by user attributes
- Detect trends across time or cohorts
- Generate insight reports instantly
Please note that this guide is about connecting Claude.ai and Claude Desktop to Refiner. It is also possible to connect Refiner MCP to Claude Code.
Connect Refiner to Claude
Section titled “Connect Refiner to Claude”Open Claude settings
Section titled “Open Claude settings”- Open Claude
- Click your profile or settings area
- Navigate to Settings
- Go to Connectors
Add a Custom Connector
Section titled “Add a Custom Connector”Since Refiner is not yet listed as a native connector, you’ll need to manually configure it:
- Click Add Custom Connector
- When prompted for a server URL, enter the one shown below
- Confirm and proceed with authentication
The Refiner MCP Server is located at:
https://app.refiner.io/v001/mcpThese steps apply to both Claude.ai (web) and Claude Desktop. Claude Desktop also supports local MCP servers.
Authenticate with Refiner
Section titled “Authenticate with Refiner”- Log into your Refiner account if required using the login credentials you normally use to connect to the Refiner dashboard
- Grant permissions for Claude to access your survey data
- Complete the connection setup
Once successful, Refiner will be available as a data source inside Claude.
Start analyzing survey data
Section titled “Start analyzing survey data”After connecting, you can immediately begin querying your survey data using natural language prompts. You’ll find a couple of examples below.
Example use cases
Section titled “Example use cases”Summarize open-text responses
Section titled “Summarize open-text responses”- “Summarize the key feedback from my latest NPS survey”
- “What are the main complaints mentioned in responses?”
Identify trends & themes
Section titled “Identify trends & themes”- “What themes appear most frequently in customer feedback?”
- “What are the top reasons users gave for low satisfaction scores?”
Segment analysis
Section titled “Segment analysis”- “Compare feedback between promoters and detractors”
- “What do users from France mention most often?”
Sentiment & insights
Section titled “Sentiment & insights”- “Analyze sentiment across all responses”
- “What actionable insights can I derive from recent feedback?”
Sample prompts
Section titled “Sample prompts”NPS feedback analysis
Section titled “NPS feedback analysis”- “What is our current NPS score?”
- “What are the key drivers behind the score according to provided open-text verbatim?”
- “How did our NPS score evolve in the last month?”
- “What are the top five things we can do to improve our NPS score?”
CSAT feedback analysis
Section titled “CSAT feedback analysis”- “What is our current CSAT score?”
- “What are the key drivers behind the score according to provided open-text verbatim?”
- “How did our CSAT score evolve in the last month?”
- “What are the top five things we can do to improve our CSAT score?”
Trend detection
Section titled “Trend detection”- “How has user sentiment changed over the past 3 months?”
- “Are there emerging issues in recent responses compared to older ones?”
- “How did our CSAT score evolve in the last month and what were the drivers for the change?”
Product insights
Section titled “Product insights”- “What are the top 5 recurring pain points mentioned by users?”
- “What features do users request most frequently?”
- “Based on the feedback, what should we prioritize improving?”
- “What frustrations do users mention about ?”
- “Get the latest survey responses and turn the list of product recommendations”
Best practices
Section titled “Best practices”- Be specific: Narrow queries produce more actionable insights
- Iterate: Refine prompts to dig deeper into patterns
- Segment data: Analyze subsets (e.g., by score, date, user segment)
- Combine queries: Ask follow-ups to expand on initial findings
Troubleshooting
Section titled “Troubleshooting”Connector not working?
Section titled “Connector not working?”- Verify the MCP URL is correct
- Ensure your Claude plan supports connectors
- Re-authenticate your Refiner account
No data returned?
Section titled “No data returned?”- Confirm your Refiner account has survey responses
- Check permissions granted during setup
Summary
Section titled “Summary”Connecting Refiner to Claude unlocks a powerful workflow for survey analysis:
- No manual exports
- No complex dashboards
- Just natural language insights, instantly
Once set up, Claude effectively becomes your AI research assistant, helping you turn raw survey data into clear, actionable decisions.