Kubit MCP Server
Warehouse-native analytics meets conversational AI
Bring the full power of Kubit directly into your AI workflow. Query, analyze, and explore your data warehouse through natural language—no complex syntax required.
What is Kubit MCP?
The Kubit MCP (Model Context Protocol) server transforms how teams interact with their analytics platform. By connecting your AI assistant to Kubit, you can:
- Explore schemas - Discover events, properties, and dimensions in natural language
- Generate reports - Create analytical queries through conversation
- Export data - Pull raw data in CSV format for deep analysis
- Search content - Find existing reports and dashboards instantly
- Ask questions - Get insights without learning query syntax
Beta Notice
This server is under active development. You may encounter bugs, performance issues, or rate limits as we continue to improve the platform.
Quick Start
What You'll Need
| Requirement | Description |
|---|
| Kubit Account | Active access to a Kubit organization |
| AI Client | MCP-compatible tool (Claude, Cursor, etc.) |
| Permissions | Schema access in your Kubit workspace |
Connection Steps
Setting up the Kubit MCP server is straightforward:
- Add the MCP server to your AI client configuration
- Use the server URL:
https://mcp.kubit.ai/mcp
- Complete OAuth authentication when prompted
- Start querying your Kubit data
Note: Check your AI client's documentation for specific MCP server setup instructions.
Authentication & Access
The server uses OAuth 2.0 authentication and respects your existing Kubit permissions. You'll only see data from schemas you already have access to—no additional permissions needed.
Your AI assistant gains access to five powerful tools:
| Tool | Purpose |
|---|
getUserContext | Initialize session and retrieve available schemas |
getSchema | Explore events, properties, and dimensions in detail |
createReport | Generate and execute analytical queries |
getRawData | Export CSV data from existing reports |
searchKubit | Find reports and dashboards across your org |
Example Conversations
Understanding User Behavior
"Show me conversion funnel for mobile app sign-ups in the last quarter"
"What are the most popular features used by premium users?"
"How has user retention changed month-over-month?"
"What are the top events by volume this week?"
"Show me user engagement trends for the last 30 days"
"Compare conversion rates across different traffic sources"
Data Discovery
"What events and properties are available in the mobile app schema?"
"Show me all custom properties for the checkout event"
"What dimensions can I use for user segmentation?"
Typical Workflow
Here's how most analysis sessions flow:
Initialize → Explore → Search → Create → Export
- Initialize - Call
getUserContext to see available schemas
- Explore - Use
getSchema to understand events and properties
- Search - Check
searchKubit for existing analyses
- Create - Generate new reports with custom queries
- Export - Pull
getRawData for external analysis
Best Practices
Crafting Effective Prompts
Be Specific
Include time ranges, events, and segments in your questions.
- "Show me users"
+ "Show me active users in the US who signed up last month"
Provide Context
Explain what you're trying to understand.
- "What's the conversion rate?"
+ "What's the conversion rate from free trial to paid for users who engaged with feature X?"
Reference Schemas
Use schema names when working with multiple data sources.
- "Show me sign-up events"
+ "In the mobile_events schema, show me sign-up events"
Break It Down
Complex analyses work better as multiple focused questions.
- "Show me everything about user behavior across all channels with retention and conversion"
+ Start with "Show me user retention by channel" then follow up
- Use
searchKubit first - Leverage existing analyses before creating new reports
- Specify date ranges - Narrow time windows improve query performance
- Export selectively - Only use
getRawData when you need detailed external analysis
Security & Compliance
| Consideration | What It Means |
|---|
| Permission Model | You can only access schemas you're authorized to view |
| AI Processing | Third-party AI models will process your query data |
| Policy Review | Confirm your organization allows AI-assisted data analysis |
Troubleshooting
Common Issues & Solutions
Authentication Failures
Verify your Kubit credentials and organization name
No Schemas Available
Check that you have access to at least one schema in Kubit
Connection Errors
Confirm you're using the correct server URL: https://mcp.kubit.ai/mcp
Report Generation Issues
Verify the schema and events you're referencing exist using getSchema
Need Help?
- Test with simple queries first to verify your connection
- Check schema access through the Kubit web interface
- Use
getSchema to confirm available events and properties
Support & Resources
Documentation
docs.kubit.ai - Complete platform documentation
Customer Success
Contact your Kubit customer success team for assistance
About Kubit
kubit.ai - Learn more about warehouse-native analytics
MCP Protocol
modelcontextprotocol.io - Explore the Model Context Protocol