Today we are launching Reforge Insights MCP. Get a demo here.
PMs use Claude to write user stories and requirements. Engineers code with Cursor's AI pair programming. Everyone's building faster than ever with AI. But here's what's broken: Your AI tools don't know your users.
Everything product teams (and the AI tools we use) do stems from understanding the customer. This has gotten more important and harder in the age of AI.
You can ask ChatGPT to create suggestions on how to "optimize the checkout flow." But without knowing that that the most frequent feedback is from your mobile users and their specific complaints about form complexity, you'll get generic non-helpful suggestions.
Engineers get smart code suggestions from Cursor, but those suggestions can't factor in the user feedback showing which features actually frustrate people.
User feedback is the missing ingredient. The difference between building fast with AI and building right.
https://fast.wistia.net/embed/iframe/jfc4eoip9c
Your User Feedback, Inside ChatGPT, Claude, Cursor, and more
Reforge Insights' new MCP (Model Context Protocol integration) changes this. Your favorite AI tools like ChatGPT, Claude, Claude Code, Cursor, and more can now directly access real time user feedback analysis—every complaint, every praise.
Reforge Insights:
Aggregates, cleans, and structures feedback across your fragmented tool set.
Analyzes it automatically with AI into specific, quantified themes.
Joins it with other important sources such as product analytics or what’s in development.
Through the Reforge Insights Model Context Protocol, your AI tools now have access to three core use-cases:
1. Smart Feedback Snippet Search
Query specific feedback example and themes
Filter by date range, user segment, or feedback source
Automatically surfaces related feedback patterns
2. Intelligent Feedback Summarization
Synthesize feedback across multiple sources: support tickets, reviews, NPS responses
Generate executive summaries: "Summarize all enterprise feedback from Q4"
Extract user language for specifications: actual quotes, not assumptions
3. Feedback Informed Document Generation
PRDs with user stories in customer language: "As a mobile user frustrated by checkout complexity..."
User Story Templates populated with real behavior patterns and pain points
Technical Specifications that reference actual user workflows and edge cases
Feature Briefs grounded in validated user needs, not internal assumptions
Each tool accesses your live Reforge Insights database—no exports, no stale data, no manual correlation.
Getting Started
New customer? If you are not a current Reforge Insights customer, get a demo here.
Existing customer? Directions on how to get started here with Cursor, Claude Code, Claude Desktop, Custom GPT, Cursor, and Windsurf.
Today we are launching Reforge Insights MCP. Get a demo here.
PMs use Claude to write user stories and requirements. Engineers code with Cursor's AI pair programming. Everyone's building faster than ever with AI. But here's what's broken: Your AI tools don't know your users.
Everything product teams (and the AI tools we use) do stems from understanding the customer. This has gotten more important and harder in the age of AI.
You can ask ChatGPT to create suggestions on how to "optimize the checkout flow." But without knowing that that the most frequent feedback is from your mobile users and their specific complaints about form complexity, you'll get generic non-helpful suggestions.
Engineers get smart code suggestions from Cursor, but those suggestions can't factor in the user feedback showing which features actually frustrate people.
User feedback is the missing ingredient. The difference between building fast with AI and building right.
https://fast.wistia.net/embed/iframe/jfc4eoip9c
Your User Feedback, Inside ChatGPT, Claude, Cursor, and more
Reforge Insights' new MCP (Model Context Protocol integration) changes this. Your favorite AI tools like ChatGPT, Claude, Claude Code, Cursor, and more can now directly access real time user feedback analysis—every complaint, every praise.
Reforge Insights:
Aggregates, cleans, and structures feedback across your fragmented tool set.
Analyzes it automatically with AI into specific, quantified themes.
Joins it with other important sources such as product analytics or what’s in development.
Through the Reforge Insights Model Context Protocol, your AI tools now have access to three core use-cases:
1. Smart Feedback Snippet Search
Query specific feedback example and themes
Filter by date range, user segment, or feedback source
Automatically surfaces related feedback patterns
2. Intelligent Feedback Summarization
Synthesize feedback across multiple sources: support tickets, reviews, NPS responses
Generate executive summaries: "Summarize all enterprise feedback from Q4"
Extract user language for specifications: actual quotes, not assumptions
3. Feedback Informed Document Generation
PRDs with user stories in customer language: "As a mobile user frustrated by checkout complexity..."
User Story Templates populated with real behavior patterns and pain points
Technical Specifications that reference actual user workflows and edge cases
Feature Briefs grounded in validated user needs, not internal assumptions
Each tool accesses your live Reforge Insights database—no exports, no stale data, no manual correlation.
Getting Started
New customer? If you are not a current Reforge Insights customer, get a demo here.
Existing customer? Directions on how to get started here with Cursor, Claude Code, Claude Desktop, Custom GPT, Cursor, and Windsurf.