Userflow

@Userflow show me all active flows and checklists currently published in our workspace, including their completion rates

Based on the available content objects in your Userflow workspace, here's what's currently published: **Active Flows:** - "Onboarding Tour v2" (ID: flow_abc123) – Published 14 days ago, 67% completion rate - "Feature Announcement: AI Assistant" (ID: flow_def456) – Published 3 days ago, 82% completion rate **Active Checklists:** - "Getting Started Guide" (ID: checklist_ghi789) – Published 21 days ago, 54% completion rate This is an illustrative example showing how the MCP would aggregate content object data. Actual completion metrics depend on your workspace's analytics configuration.

This example demonstrates read-only content discovery using the Get a Content Object tool. Requires API key with read permissions. Userflow's API returns content metadata but completion rates may require additional analytics endpoints. Useful for auditing what end-users currently see in your product.

@Userflow create a new user account for sarah.chen@example.com with attributes role=product_manager, team=growth, signup_date=2025-01-15

User created successfully in Userflow: **User ID:** user_jkl012 **Email:** sarah.chen@example.com **Attributes:** - role: product_manager - team: growth - signup_date: 2025-01-15T00:00:00Z This user will now be eligible for flows and checklists targeting the "product_manager" role or "growth" team. If this user ID already existed, the attributes would have been merged with existing data rather than creating a duplicate. This is an illustrative example of the Create or Update a User operation.

This example shows user provisioning via the Create or Update a User tool. Side-effect: immediately makes the user visible to Userflow's targeting rules, potentially triggering flows. The tool merges attributes if the user already exists, so it's safe to call repeatedly. Requires API key with write permissions.

@Userflow analyze our "Getting Started Guide" checklist and tell me which tasks users are abandoning most often, then suggest improvements

I've retrieved the "Getting Started Guide" checklist (ID: checklist_ghi789) with its 5 tasks: 1. Connect your data source – 89% completion 2. Invite team members – 76% completion 3. Create your first dashboard – 52% completion ⚠️ 4. Set up alerts – 31% completion ⚠️ 5. Schedule a report – 28% completion ⚠️ **Drop-off analysis:** Tasks 3-5 show steep abandonment (52% → 31% → 28%). This suggests users lose momentum after the social/setup phase. **Recommendations:** - Add inline help or video tutorial at Task 3 (dashboard creation) - Consider breaking Task 4 into smaller steps - Reorder tasks so "Schedule a report" comes before "Set up alerts" (reporting may feel more immediately valuable) This is an illustrative synthesis combining Get a Content Version data with AI reasoning about user behavior patterns.

This example pairs the Get a Content Version tool with AI analysis to surface actionable insights. The MCP provides task structure; the AI infers drop-off patterns and suggests UX improvements. Actual task completion data would come from Userflow's analytics, not the content metadata alone. Demonstrates how Switchy's AI can turn raw MCP data into strategic recommendations.

When Userflow wins for product-led onboarding at 10-person teams

A 10-person SaaS startup ships a new feature every two weeks and needs onboarding flows that stay in sync with user state. Userflow is the right call here because the MCP lets you create or update users and groups from your backend as signups happen, then trigger flows based on real-time attributes. The 18 tools cover the full lifecycle: you can push user data when someone converts, delete sessions when they churn, and retrieve content versions to audit what's live. The API key auth means your ops person can wire this up in an afternoon without OAuth red tape. If your team is over 50 people or you're running hundreds of flows, you'll hit the ceiling where a dedicated product analytics stack makes more sense. For early-stage teams shipping fast and iterating on onboarding, this MCP keeps your flows honest without a separate integration project.

Why Userflow works for CS teams managing trial-to-paid transitions

A 6-person customer success team at a B2B SaaS company needs to track which trial accounts have completed onboarding checklists before the sales handoff. Userflow is a solid fit because the MCP exposes tools to retrieve content sessions and check task completion without logging into the UI. Your CS lead can query checklist progress during weekly pipeline reviews, update group attributes when an account converts, and delete stale sessions when trials expire. The group-level operations (create, update, delete) map directly to how CS thinks about accounts, not individual users. The threshold: if you're managing more than 200 active trials at once, the manual query workflow gets tedious and you'll want a BI tool pulling this data in bulk. For smaller CS teams who need quick answers during live calls, this MCP gives you the data without building a custom dashboard.

When Userflow handles compliance deletion for support teams

A 4-person support team at a European SaaS company gets 3-5 GDPR deletion requests per month and needs to scrub user data from onboarding surveys. Userflow is the right tool because the MCP includes delete operations for users, groups, and content sessions—all the entities that store personal data. When a deletion request comes in, your support engineer can run the delete user tool, which cascades to attributes, events, and flow history in one call. The delete content session tool handles survey answers separately if you need granular control. The API key auth means you can script this into your compliance runbook without involving engineering. The limit: if you're processing more than 50 deletions per month, you'll want a dedicated privacy platform that batches requests across all your tools. For small teams with occasional requests, this MCP closes the loop without a separate compliance project.