Spec-Driven Development
Your users already wrote
the spec.
ProductSights clusters hundreds of user voices into structured problem context. Your AI coding assistant turns that context into specs grounded in real evidence — not a PM's two-paragraph summary.
No Jira. No ticket handoff. Feedback flows directly to the people building.
Running in production
Feedback → Spec → Shipped
New MCP tools for your IDE
get_spec_contextProblem statement, user quotes, acceptance criteria signals — everything your AI needs
update_cluster_statusLink your branch, mark shipped — close the loop without leaving your editor
get_cluster_detailFull discovery context: hypotheses, open questions, affected segments
npx @productsights/mcp-serverWhy specs from ProductSights are different
- Grounded in 10s–100s of real user quotes, not a PM summary
- Include severity distribution, affected segments, trend direction
- Living documents — new feedback updates the context automatically
Connects with your existing tools
01 — Capabilities
From feedback noise
to product clarity
Collect
Ingest feedback from Slack, Intercom, Zendesk, email, app reviews, and in-app widgets — all into one funnel.
Understand
AI classifies, deduplicates, and scores every piece of feedback — so you see themes, not noise.
Explore
Interactive dashboards for trends, sentiment, and top requests. Ask questions in natural language and get instant answers.
Act
Push triaged insights to Jira or Productboard, and query feedback from your IDE via MCP — insights where you already work.
MCP Integration
Product intelligence
where you already work
ProductSights uses the Model Context Protocol to connect your feedback pipeline with AI coding tools and any MCP-compatible data source — both ways.
Query from your IDE
ProductSights → AI tools
Install the MCP server and query your product insights directly from AI coding tools. Your team builds informed by real user needs — without context switching.
get_spec_context— Cluster data shaped for AI spec generationget_cluster_detail— Full cluster with evidence, quotes, and discovery contextupdate_cluster_status— Link your branch/PR and track progresssearch_insights— Search by keyword, category, or sentimentget_top_problems— Top user problems grouped into clustersfind_insights_by_meaning— Semantic search across all feedbackQuick install
npx @productsights/mcp-serverIngest from any MCP server
Any MCP server → ProductSights
Use any MCP-compatible server as a feedback source. ProductSights connects to your server, calls a tool you configure, and routes the output through the full AI triage pipeline — classification, sentiment, priority, and deduplication.
Output mapping modes
rawjson-arrayjson-path02 — Pricing
Pricing that scales with
your feedback
Start for free. Upgrade when your product grows.
Free
$0/mo
Ideal for individuals starting to collect feedback.
- 1 source
- 100 insights / month
- 1 seat
- Manual sync
Pro
$49/mo
For small teams needing more sources and volume.
- 5 sources
- 2,000 insights / month
- 3 seats included (+$15/extra seat)
- Auto-sync
- Priority email support
Team
$149/mo
For growing product teams with higher volume.
- 15 sources
- 10,000 insights / month
- 10 seats included (+$12/extra seat)
- Advanced rules engine
- Custom field mapping
03 — FAQ
Frequently asked questions
Ready to know exactly
what to build?
Join product teams who compete on insight, not just execution speed.