> ## Documentation Index
> Fetch the complete documentation index at: https://clickhouse.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# 如何使用 Agno 和 ClickHouse MCP 服务器构建 AI 智能体

> 了解如何使用 Agno 和 ClickHouse MCP 服务器构建 AI 智能体

在本指南中，你将学习如何构建一个 [Agno](https://github.com/agno-agi/agno) AI 智能体，并借助 [ClickHouse MCP 服务器](https://github.com/ClickHouse/mcp-clickhouse) 与 [ClickHouse SQL playground](https://sql.clickhouse.com/) 交互。

<Info>
  **示例 notebook**

  你可以在 [examples repository](https://github.com/ClickHouse/examples/blob/main/ai/mcp/agno/agno.ipynb) 中找到这个示例 notebook。
</Info>

<div id="prerequisites">
  ## 前置条件
</div>

* 你的系统上需要已安装 Python。
* 你的系统上需要已安装 `pip`。
* 你需要 Anthropic API key，或其他 LLM 提供商的 API key。

你可以在 Python REPL 中或通过脚本运行以下步骤。

<Steps>
  <Step title="安装库" id="install-libraries">
    运行以下命令安装 Agno 库：

    ```python theme={null}
    pip install -q --upgrade pip
    pip install -q agno
    pip install -q ipywidgets
    ```
  </Step>

  <Step title="设置凭证" id="setup-credentials">
    接下来，您需要提供您的 Anthropic API 密钥：

    ```python theme={null}
    import os, getpass
    os.environ["ANTHROPIC_API_KEY"] = getpass.getpass("Enter Anthropic API Key:")
    ```

    ```response title="Response" theme={null}
    Enter Anthropic API Key: ········
    ```

    <Info>
      **使用其他 LLM 提供商**

      如果你没有 Anthropic API 密钥，但想使用其他 LLM 提供商，
      可以在 [Agno 文档](https://docs.agno.com/models/overview)中查看设置凭据的说明。
    </Info>

    接下来，定义连接 ClickHouse SQL playground 所需的凭据：

    ```python theme={null}
    env = {
        "CLICKHOUSE_HOST": "sql-clickhouse.clickhouse.com",
        "CLICKHOUSE_PORT": "8443",
        "CLICKHOUSE_USER": "demo",
        "CLICKHOUSE_PASSWORD": "",
        "CLICKHOUSE_SECURE": "true"
    }
    ```
  </Step>

  <Step title="初始化 MCP 服务器和 Agno agent" id="initialize-mcp-and-agent">
    现在将 ClickHouse MCP 服务器配置为指向 ClickHouse SQL playground，
    并初始化 Agno agent，然后向它提一个问题：

    ```python theme={null}
    from agno.agent import Agent
    from agno.tools.mcp import MCPTools
    from agno.models.anthropic import Claude
    ```

    ```python theme={null}
    async with MCPTools(command="uv run --with mcp-clickhouse --python 3.13 mcp-clickhouse", env=env, timeout_seconds=60) as mcp_tools:
        agent = Agent(
            model=Claude(id="claude-3-5-sonnet-20240620"),
            markdown=True,
            tools = [mcp_tools]
        )
    await agent.aprint_response("What's the most starred project in 2025?", stream=True)
    ```

    ```response title="Response" theme={null}
    ▰▱▱▱▱▱▱ Thinking...
    ┏━ Message ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
    ┃                                                                                                                 ┃
    ┃ What's the most starred project in 2025?                                                                        ┃
    ┃                                                                                                                 ┃
    ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
    ┏━ Tool Calls ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
    ┃                                                                                                                 ┃
    ┃ • list_tables(database=github, like=%)                                                                          ┃
    ┃ • run_select_query(query=SELECT                                                                                 ┃
    ┃     repo_name,                                                                                                  ┃
    ┃     SUM(count) AS stars_2025                                                                                    ┃
    ┃ FROM github.repo_events_per_day                                                                                 ┃
    ┃ WHERE event_type = 'WatchEvent'                                                                                 ┃
    ┃     AND created_at >= '2025-01-01'                                                                              ┃
    ┃     AND created_at < '2026-01-01'                                                                               ┃
    ┃ GROUP BY repo_name                                                                                              ┃
    ┃ ORDER BY stars_2025 DESC                                                                                        ┃
    ┃ LIMIT 1)                                                                                                        ┃
    ┃                                                                                                                 ┃
    ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
    ┏━ Response (34.9s) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
    ┃                                                                                                                 ┃
    ┃ To answer your question about the most starred project in 2025, I'll need to query the ClickHouse database.     ┃
    ┃ However, before I can do that, I need to gather some information and make sure we're looking at the right data. ┃
    ┃ Let me check the available databases and tables first.Thank you for providing the list of databases. I can see  ┃
    ┃ that there's a "github" database, which is likely to contain the information we're looking for. Let's check the ┃
    ┃ tables in this database.Now that we have information about the tables in the github database, we can query the  ┃
    ┃ relevant data to answer your question about the most starred project in 2025. We'll use the repo_events_per_day ┃
    ┃ table, which contains daily event counts for each repository, including star events (WatchEvents).              ┃
    ┃                                                                                                                 ┃
    ┃ Let's create a query to find the most starred project in 2025:Based on the query results, I can answer your     ┃
    ┃ question about the most starred project in 2025:                                                                ┃
    ┃                                                                                                                 ┃
    ┃ The most starred project in 2025 was deepseek-ai/DeepSeek-R1, which received 84,962 stars during that year.     ┃
    ┃                                                                                                                 ┃
    ┃ This project, DeepSeek-R1, appears to be an AI-related repository from the DeepSeek AI organization. It gained  ┃
    ┃ significant attention and popularity among the GitHub community in 2025, earning the highest number of stars    ┃
    ┃ for any project during that year.                                                                               ┃
    ┃                                                                                                                 ┃
    ┃ It's worth noting that this data is based on the GitHub events recorded in the database, and it represents the  ┃
    ┃ stars (WatchEvents) accumulated specifically during the year 2025. The total number of stars for this project   ┃
    ┃ might be higher if we consider its entire lifespan.                                                             ┃
    ┃                                                                                                                 ┃
    ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
    ```
  </Step>
</Steps>