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docs/use-cases/AI_ML/MCP/ai_agent_libraries/_category_.json

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"type": "doc",
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"id": "use-cases/AI_ML/MCP/ai_agent_libraries/index"
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}
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}
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}

docs/use-cases/AI_ML/MCP/ai_agent_libraries/chainlit.md

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show_related_blogs: true
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# Chainlit and the ClickHouse MCP Server
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# How to build an AI agent with Chainlit and the ClickHouse MCP Server
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This guide explores how to combine Chainlit's powerful chat interface framework
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with the ClickHouse Model Context Protocol (MCP) Server to create interactive data

docs/use-cases/AI_ML/MCP/ai_agent_libraries/copilotkit.md

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show_related_blogs: true
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# CopilotKit and the ClickHouse MCP Server
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# How to build an AI agent with CopilotKit and the ClickHouse MCP Server
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This is an example of how to build an agentic application using data stored in
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ClickHouse. It uses the [ClickHouse MCP Server](https://github.com/ClickHouse/mcp-clickhouse)

docs/use-cases/AI_ML/MCP/ai_agent_libraries/slackbot.md

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# How to build a slackbot agent using ClickHouse MCP Server
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# How to build a SlackBot agent using ClickHouse MCP Server
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In this guide, you'll learn how to build a [SlackBot](https://slack.com/intl/en-gb/help/articles/202026038-An-introduction-to-Slackbot) agent.
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This bot allows you to ask questions about your ClickHouse data directly from Slack, using natural language. It uses the

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