如何使用 Agno 和 ClickHouse MCP Server 构建 AI Agent
在本指南中，你将学习如何构建一个 Agno AI agent，使其能够通过 ClickHouse 的 MCP Server 与 ClickHouse 的 SQL playground 进行交互。
示例 Notebook
该示例可以在 示例仓库 中以 Notebook 的形式找到。
前置条件
- 您需要在系统上安装 Python。
- 您需要在系统上安装
pip。 - 您需要 Anthropic API 密钥或其他 LLM 提供商的 API 密钥。
您可以通过 Python REPL 或脚本运行以下步骤。
配置凭证
接下来，您需要提供 Anthropic API 密钥：
import os, getpass
os.environ["ANTHROPIC_API_KEY"] = getpass.getpass("Enter Anthropic API Key:")
Enter Anthropic API Key: ········
使用其他 LLM 提供商
如果你没有 Anthropic API 密钥，并且想要使用其他 LLM 提供商， 可以在 Agno 文档 中找到设置凭据的说明。
接下来，定义用于连接 ClickHouse SQL playground 的凭据：
env = {
"CLICKHOUSE_HOST": "sql-clickhouse.clickhouse.com",
"CLICKHOUSE_PORT": "8443",
"CLICKHOUSE_USER": "demo",
"CLICKHOUSE_PASSWORD": "",
"CLICKHOUSE_SECURE": "true"
}
初始化 MCP 服务器和 Agno 代理
现在配置 ClickHouse MCP 服务器指向 ClickHouse SQL 演练场, 并初始化 Agno 代理,然后向其提问:
from agno.agent import Agent
from agno.tools.mcp import MCPTools
from agno.models.anthropic import Claude
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)
▰▱▱▱▱▱▱ 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. ┃
┃ ┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
