Kubit

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.

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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.

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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:

1. Add the MCP server to your AI client configuration
2. Use the server URL: https://mcp.kubit.ai/mcp
3. Complete OAuth authentication when prompted
4. 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.

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Tools & Capabilities

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

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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?"

Product Performance

"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?"

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Typical Workflow

Here's how most analysis sessions flow:

Initialize → Explore → Search → Create → Export

1. Initialize - Call getUserContext to see available schemas
2. Explore - Use getSchema to understand events and properties
3. Search - Check searchKubit for existing analyses
4. Create - Generate new reports with custom queries
5. Export - Pull getRawData for external analysis

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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

Performance Optimization

• 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

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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

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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