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Как создать ИИ-агента на LangChain/LangGraph с помощью MCP-сервера ClickHouse.

В этом руководстве вы узнаете, как создать ИИ-агента на LangChain/LangGraph, который может взаимодействовать с SQL-песочницей ClickHouse через MCP-сервер ClickHouse.

Предварительные требования

  • В системе должен быть установлен Python.
  • В системе должен быть установлен pip.
  • Вам понадобится API key Anthropic или API key другого провайдера LLM

Вы можете выполнить следующие шаги либо в Python REPL, либо с помощью скрипта.

Установка библиотек

Установите необходимые библиотеки, выполнив следующие команды:

pip install -q --upgrade pip
pip install -q langchain-mcp-adapters langgraph "langchain[anthropic]"

Настройка учетных данных

Далее вам нужно указать API-ключ Anthropic:

import os, getpass
os.environ["ANTHROPIC_API_KEY"] = getpass.getpass("Enter Anthropic API Key:")
Responseresponse
Enter Anthropic API Key: ········

Инициализируйте MCP-сервер

Теперь настройте MCP-сервер ClickHouse для работы с песочницей ClickHouse SQL:

from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client

server_params = StdioServerParameters(
    command="uv",
    args=[
        "run",
        "--with", "mcp-clickhouse",
        "--python", "3.13",
        "mcp-clickhouse"
    ],
    env={
        "CLICKHOUSE_HOST": "sql-clickhouse.clickhouse.com",
        "CLICKHOUSE_PORT": "8443",
        "CLICKHOUSE_USER": "demo",
        "CLICKHOUSE_PASSWORD": "",
        "CLICKHOUSE_SECURE": "true"
    }
)

Настройте обработчик потока

При работе с Langchain и MCP-сервером ClickHouse результаты запроса часто возвращаются в виде потока данных, а не одним ответом. Для больших наборов данных или сложных аналитических запросов, обработка которых может занять некоторое время, важно настроить обработчик потока. Без надлежащей обработки с этим потоковым выводом может быть сложно работать в приложении.

Настройте обработчик для потокового вывода, чтобы его было проще использовать:

class UltraCleanStreamHandler:
    def __init__(self):
        self.buffer = ""
        self.in_text_generation = False
        self.last_was_tool = False
        
    def handle_chunk(self, chunk):
        event = chunk.get("event", "")
        
        if event == "on_chat_model_stream":
            data = chunk.get("data", {})
            chunk_data = data.get("chunk", {})
            
            # Only handle actual text content, skip tool invocation streams
            if hasattr(chunk_data, 'content'):
                content = chunk_data.content
                if isinstance(content, str) and not content.startswith('{"'):
                    # Add space after tool completion if needed
                    if self.last_was_tool:
                        print(" ", end="", flush=True)
                        self.last_was_tool = False
                    print(content, end="", flush=True)
                    self.in_text_generation = True
                elif isinstance(content, list):
                    for item in content:
                        if (isinstance(item, dict) and 
                            item.get('type') == 'text' and 
                            'partial_json' not in str(item)):
                            text = item.get('text', '')
                            if text and not text.startswith('{"'):
                                # Add space after tool completion if needed
                                if self.last_was_tool:
                                    print(" ", end="", flush=True)
                                    self.last_was_tool = False
                                print(text, end="", flush=True)
                                self.in_text_generation = True
                                
        elif event == "on_tool_start":
            if self.in_text_generation:
                print(f"\n🔧 {chunk.get('name', 'tool')}", end="", flush=True)
                self.in_text_generation = False
                
        elif event == "on_tool_end":
            print(" ✅", end="", flush=True)
            self.last_was_tool = True

Вызовите агента

Наконец, обратитесь к своему агенту и спросите, кто внёс больше всего кода в ClickHouse:

async with stdio_client(server_params) as (read, write):
    async with ClientSession(read, write) as session:
        await session.initialize()
        tools = await load_mcp_tools(session)
        agent = create_react_agent("anthropic:claude-sonnet-4-0", tools)
        
        handler = UltraCleanStreamHandler()        
        async for chunk in agent.astream_events(
            {"messages": [{"role": "user", "content": "Who's committed the most code to ClickHouse?"}]}, 
            version="v1"
        ):
            handler.handle_chunk(chunk)
            
        print("\n")

Вы должны увидеть ответ, похожий на приведённый ниже:

Responseresponse
I'll help you find who has committed the most code to ClickHouse by exploring the available databases and tables to locate git commit data.
🔧 list_databases ✅ I can see there's a `git` database which likely contains git commit information. Let me explore the tables in that database:
🔧 list_tables ✅ Perfect! I can see the `clickhouse_commits` table in the git database contains ClickHouse commit data with 80,644 commits. This table has information about each commit including the author, lines added/deleted, files modified, etc. Let me query this table to find who has committed the most code based on different metrics.
🔧 run_select_query ✅ Let me also look at just the lines added to see who has contributed the most new code:
🔧 run_select_query ✅ Based on the ClickHouse git commit data, **Alexey Milovidov** has committed the most code to ClickHouse by several measures:

## Key Statistics:

1. **Most Total Lines Changed**: Alexey Milovidov with **1,696,929 total lines changed** (853,049 added + 843,880 deleted)
2. **Most Lines Added**: Alexey Milovidov with **853,049 lines added**
3. **Most Commits**: Alexey Milovidov with **15,375 commits**
4. **Most Files Changed**: Alexey Milovidov with **73,529 files changed**

## Top Contributors by Lines Added:

1. **Alexey Milovidov**: 853,049 lines added (15,375 commits)
2. **s-kat**: 541,609 lines added (50 commits) 
3. **Nikolai Kochetov**: 219,020 lines added (4,218 commits)
4. **alesapin**: 193,566 lines added (4,783 commits)
5. **Vitaly Baranov**: 168,807 lines added (1,152 commits)

Alexey Milovidov is clearly the most prolific contributor to ClickHouse, which makes sense as he is one of the original creators and lead developers of the project. His contribution dwarfs others both in terms of total code volume and number of commits, with nearly 16,000 commits and over 850,000 lines of code added to the project.
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