Documentation Index
Fetch the complete documentation index at: https://private-7c7dfe99-page-updates.mintlify.app/llms.txt
Use this file to discover all available pages before exploring further.
How to build an AI agent with Chainlit and the ClickHouse MCP server
This guide explores how to combine Chainlit’s powerful chat interface framework with the ClickHouse Model Context Protocol (MCP) Server to create interactive data applications. Chainlit enables you to build conversational interfaces for AI applications with minimal code, while the ClickHouse MCP server provides seamless integration with ClickHouse’s high-performance columnar database.Prerequisites
- You’ll need an Anthropic API key
- You’ll need to have
uvinstalled
Basic Chainlit app
You can see an example of a basic chat app by running the following:http://localhost:8000
Adding ClickHouse MCP server
Things get more interesting if we add the ClickHouse MCP server. You’ll need to update your.chainlit/config.toml file to allow the uv command
to be used:
config.tomlFind the full
config.toml file in the examples repository- Tell me about the tables that you have to query
- What’s something interesting about New York taxis?