Formbricks

@Formbricks show me all active surveys in our production environment and their completion rates from the last 30 days

Based on your Formbricks environment, here are your active surveys: • Product Feedback Survey (ID: srv_abc123) – 847 displays, 312 completions (36.8% rate) • Onboarding Experience (ID: srv_def456) – 1,203 displays, 891 completions (74.1% rate) • Feature Request Form (ID: srv_ghi789) – 421 displays, 89 completions (21.1% rate) The onboarding survey shows strong engagement. The feature request form may need review—low completion suggests friction in the question flow or targeting.

This example demonstrates read-heavy data retrieval across surveys. Requires API key with read access to surveys and responses. Completion rate calculations are illustrative—actual metrics depend on your survey configuration and display logic. Rate limits apply to bulk survey queries.

@Formbricks create a new NPS survey targeting users who completed onboarding in the last 7 days, asking how likely they are to recommend us

I've created your NPS survey (ID: srv_nps_001) with the following configuration: • Question: "How likely are you to recommend our product to a colleague?" (0-10 scale) • Targeting: Users with 'onboarding_completed' attribute from last 7 days • Trigger: 24 hours after onboarding completion • Status: Draft (ready for review) The survey is configured but not yet live. You'll need to activate it in your Formbricks dashboard to start collecting responses. I've set conservative targeting to avoid survey fatigue.

This showcases survey creation with attribute-based targeting. The MCP creates the survey structure but leaves it in draft status—you must manually activate it to prevent accidental live deployment. Requires write permissions and assumes the 'onboarding_completed' attribute class already exists in your environment.

@Formbricks analyze the last 50 responses to our customer satisfaction survey and identify the top 3 pain points mentioned in open-ended feedback

I've retrieved 50 recent responses from your customer satisfaction survey (srv_csat_main). Here are the top 3 pain points from open-ended feedback: 1. **Slow loading times** (mentioned in 18 responses) – Users report dashboard lag, especially with large datasets 2. **Confusing navigation** (mentioned in 12 responses) – Difficulty finding settings and export features 3. **Limited integrations** (mentioned in 9 responses) – Requests for Slack, Zapier, and CRM connections These themes emerged from text analysis of the 'additional_comments' field. Consider prioritizing performance optimization and navigation UX in your next sprint.

This example pairs Formbricks data retrieval with AI reasoning to synthesize qualitative feedback. The MCP fetches raw response data; the AI performs the thematic analysis. Results quality depends on response volume and how users phrase feedback. Requires read access to survey responses and handles personally identifiable information—ensure compliance with your data policies.

When Formbricks beats your CRM's native survey for product demos

A 6-person B2B SaaS sales team runs 40 demos a month and wants feedback within 5 minutes of each call ending. Formbricks wins here because you can trigger surveys via webhook the moment a Zoom call ends, then pipe responses back into your CRM as contact attributes. The Create Survey Response and Create Contact tools let you build this loop in one Switchy workflow—no Zapier tax, no form-builder UI. The threshold: if you're already paying for a full customer-data platform that does post-call surveys natively, Formbricks is overkill. But if your CRM's survey module is clunky or you want programmable question logic based on demo type, this MCP gives you that control without hiring a forms engineer.

How a 3-person product team uses Formbricks to segment feature requests

A startup product trio collects feature requests from 200 beta users every sprint and needs to tag each response by user segment (enterprise vs. SMB, power user vs. casual). Formbricks' Create Attribute Class and Create Action Class tools let you define custom taxonomies and trigger follow-up questions based on prior answers—all scriptable in Switchy. You build the survey once, then let the MCP handle branching logic and attribute writes as responses come in. This beats a Google Form because the segmentation happens inline, not in a post-processing spreadsheet. The trade-off: if your user base is under 50 people and you're doing one-off interviews, a shared Notion doc is faster. Formbricks pays off when you need repeatable, structured feedback at scale.

When to use Formbricks to prove your help docs are working

A 10-person support team ships new help articles every week and wants to measure whether users find answers before opening tickets. Formbricks' Create Display and Create Webhook tools let you show a micro-survey at the bottom of each doc page, then push results to your support dashboard in real time. The MCP's 31 tools give you granular control over survey triggers (time on page, scroll depth, exit intent) without touching frontend code. This setup works if your docs site can fire webhooks and you have a developer who can map survey IDs to article slugs. If your support volume is under 100 tickets a month, the juice isn't worth the squeeze—just ask in Slack. But at 500+ tickets, this data tells you which articles to retire and which to promote.