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Test product concepts with synthetic consumers and generate purchase-intent reports.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "ssr-concept-mcp" yet — see the docs or source repo.
Simulate 30 target users to evaluate this AI bookkeeping app concept for freelancers. Based on their free-text reactions, output purchase-intent scores, main concerns, the most appealing selling points, and a grouped summary by user type.
A concept-testing report with purchase-intent distribution, user concerns, key selling points, and segmented audience insights.
Have synthetic consumers evaluate these two product messaging directions: A emphasizes saving time, B emphasizes reducing cost. Analyze which message increases purchase intent more, and provide reasons and representative feedback summaries.
A comparison report showing purchase-intent differences, reasons, and representative user feedback for both messaging options.
For this subscription-based health management product, simulate three consumer types: price-sensitive, privacy-focused, and results-focused. Output their reactions, purchase barriers, churn risks, and optimization recommendations.
A risk analysis organized by consumer type, including purchase barriers, churn risks, and improvement recommendations.
Query a semantic concept graph for codebase invariants and cross-cutting facts.
Read Jira and Confluence to generate QA artifacts and coverage analysis.
Synthesize user research into themes, insights, and prioritized recommendations.
Validate startup ideas using behavioral signals to uncover demand and inform sales decisions.
Generate SEO briefs, analyze semantic coverage, and manage briefs in chat.
Score companies against your ICP using firmographic and signal data.