Synthesize Customer Feedback into Ranked Pain Points with MCP
This article introduces a tool called feedback-synthesis-mcp that collects customer feedback from multiple sources, extracts themes, clusters them, and ranks the pain points by severity and frequency.
Why it matters
This tool can help product teams efficiently synthesize and prioritize customer feedback from multiple sources, which is a common challenge for growing companies.
Key Points
- 1Collects feedback from GitHub Issues, Hacker News, and App Store reviews
- 2Runs a 3-stage LLM pipeline to synthesize the feedback into ranked pain clusters
- 3Provides additional tools for quick single-source extraction, search, and sentiment analysis
Details
The feedback-synthesis-mcp tool is a server that can aggregate customer feedback from various sources, including GitHub Issues, Hacker News, and App Store reviews. It uses a 3-stage LLM pipeline to process the feedback: 1) Batch extraction to identify themes, sentiment, and severity; 2) Theme clustering to deduplicate and group similar feedback; and 3) Pain synthesis to rank the pain points by severity and frequency, describe them, and link to the original evidence. The tool provides several APIs, including synthesize_feedback, get_pain_points, search_feedback, and get_sentiment_trends, to help product teams quickly understand and prioritize customer pain points.
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