Mopinion

@Mopinion show me all feedback submitted in the last 7 days with sentiment scores below 3 out of 5

Retrieved 47 feedback entries from the past week with low sentiment scores. Common themes: 22 mention slow page load times on the checkout flow, 15 report confusion around the refund policy link, 8 cite mobile navigation issues on product detail pages. Average sentiment: 2.1/5. Most recent entry submitted 3 hours ago flagged a broken 'Add to Cart' button on Safari iOS.

This example demonstrates the MCP's ability to filter feedback by date range and sentiment threshold. Requires read access to your Mopinion deployment's feedback datasets. Response time depends on total feedback volume — accounts with 10k+ monthly submissions may see 3-5 second delays on broad queries.

@Mopinion create a new feedback form for our mobile app onboarding flow, targeting users who completed signup in the last 24 hours

Created feedback form 'Mobile Onboarding Survey' (ID: mf_8x2k9p) with default question set: NPS score, open text for friction points, and a 5-star ease-of-use rating. Targeting rule applied: users with 'signup_completed' event timestamp within 24 hours. Form is live and will appear on next app session for qualifying users. Preview link generated for internal testing.

This write operation requires admin-level API key permissions in Mopinion. The MCP creates forms with sensible defaults but cannot customize question logic or conditional branching without additional parameters. Always verify targeting rules in the Mopinion dashboard before pushing to production traffic.

@Mopinion analyze feedback trends for our pricing page over the last quarter and draft three actionable recommendations for the product team

Analyzed 312 feedback entries tagged 'pricing_page' from Q1 2025. Key trends: 41% mention confusion between Pro and Enterprise tier features, 28% request annual billing discount visibility, 18% cite competitor pricing comparisons. Sentiment declined 0.7 points month-over-month in March. Recommendations: (1) Add a feature comparison table above fold to clarify tier differences. (2) Surface annual discount savings (20%) in the monthly toggle UI. (3) Consider a 'Why us?' section addressing the top 3 competitor objections surfaced in open text.

This synthesis example combines the MCP's feedback retrieval with the AI's pattern recognition and strategic reasoning. The quality of recommendations depends on feedback volume and tagging consistency in your Mopinion setup. Works best when feedback forms include structured tags (page, feature area) rather than relying solely on free-text parsing.

When Mopinion fits a lean product team's feedback loop

A 5-person product team ships weekly and collects in-app feedback through Mopinion's widgets. They spend 30 minutes each Monday reviewing sentiment trends and tagging feature requests. This MCP works if your team already uses Mopinion as the single source of truth for user feedback and you need AI to summarize themes or flag outliers during standup. The API key auth means any team member can connect their workspace without IT approval. The trade-off: if you're aggregating feedback from multiple sources (Intercom, Zendesk, email), this MCP only sees Mopinion data, so your AI summaries will be incomplete. Best fit for teams under 10 people who've standardized on Mopinion and want faster triage, not cross-platform synthesis.

Mopinion for account health checks at scale

A 3-person customer success team manages 40 B2B accounts and uses Mopinion to track NPS and feature satisfaction per account. Two weeks before each QBR, they pull feedback history to build account health decks. This MCP is the right call if you're already tagging feedback by account ID in Mopinion and you need AI to draft account summaries or compare sentiment quarter-over-quarter. The limitation: if your QBR data also lives in Salesforce, Gainsight, or support tickets, you'll need additional MCPs to get a full picture. This works when Mopinion is your primary feedback layer and you're building 10+ similar reports each quarter. If you only run QBRs twice a year, manual export is faster.

When Mopinion doesn't replace dedicated research tools

A 2-person design team runs moderated usability tests and collects post-session feedback through Mopinion forms. They want AI to pull quotes and sentiment during synthesis. This MCP is borderline: it works if your usability feedback lives entirely in Mopinion and you're running 5+ tests per sprint. But most design teams use Dovetail, Notion, or Airtable to organize session notes, screen recordings, and participant metadata. Mopinion captures the survey layer, not the qualitative depth. If your synthesis process involves coding transcripts or linking feedback to specific UI flows, this MCP won't replace your research stack. Use it only if Mopinion is already your single repository and you need quick sentiment rollups, not deep thematic analysis.