AI & ML Integration
Databend enables powerful AI and ML capabilities through two complementary approaches: build custom AI functions with your own infrastructure, or create conversational data experiences using natural language.
External Functions - The Recommended Approach
External functions enable you to connect your data with custom AI/ML infrastructure, providing maximum flexibility and performance for AI workloads.
| Feature | Benefits |
|---|---|
| Custom Models | Use any open-source or proprietary AI/ML models |
| GPU Acceleration | Deploy on GPU-equipped machines for faster inference |
| Data Privacy | Keep your data within your infrastructure |
| Scalability | Independent scaling and resource optimization |
| Flexibility | Support for any programming language and ML framework |
MCP Server - Natural Language Data Interaction
The Model Context Protocol (MCP) server enables AI assistants to interact with your Databend database using natural language, perfect for building conversational BI tools. On Databend Cloud, point your AI client at the hosted MCP server and sign in through your browser — no DSN or local install required.
| Feature | Benefits |
|---|---|
| Natural Language | Query your data using plain English |
| AI Assistant Integration | Works with Claude, Cursor, Codex, and custom agents |
| OAuth Sign-In | Connect with a single URL; no token to manage |
Getting Started
External Functions Guide - Learn how to create and deploy custom AI functions with practical examples and implementation guidance
MCP Client Integration - Connect your AI assistant to the hosted Databend Cloud MCP server, or run the local mcp-databend server for self-hosted Databend
MCP Server Guide - Build a conversational BI tool using the local mcp-databend server (also the way to connect self-hosted Databend)