How to Use the Baidu Analytics / 百度统计 MCP in LangChain

Pull Baidu Analytics / 百度统计 data directly into LangChain chains for automated traffic reporting and site monitoring.

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Connect Baidu Analytics / 百度统计 MCP to LangChain

Create your Vinkius account to connect Baidu Analytics / 百度统计 to LangChain and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Baidu Analytics / 百度统计 with LangChain

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Chain Baidu Analytics / 百度统计 metrics

Feed live traffic data from `get_daily_trend` or `get_realtime_metrics` directly into your agent's reasoning loop. Since LangChain treats these as standard tools, the output of one call informs the next step of your chain. Your agent decides which metric to pull based on the previous result. It chains `list_sites` with `get_page_rankings` to identify high-performing content without manual intervention.

Trace Baidu Analytics / 百度统计 data flows

Monitor exactly how your agent interprets site traffic by using LangSmith to log every tool call. You see the raw JSON returned from `get_source_data` and how it influences the final response. This MCP server gives you a clear audit trail for every query. You catch bad data before it hits your production reports.

Connect multiple analytics sources

Combine the Baidu Analytics / 百度统计 MCP Server with your existing vector stores or SQL databases in one LangChain pipeline. Your agent pulls data from your internal database and compares it against live visitor stats. You avoid context switching by keeping all logic inside one graph. It’s all about building complex reasoning pipelines that actually work.

Setup guide

Set up Baidu Analytics / 百度统计 MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Baidu Analytics / 百度统计 tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "baidu-analytics-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent Baidu Analytics / 百度统计 transactions"
    })
    print(result["messages"][-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Baidu Analytics / 百度统计. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Baidu Analytics / 百度统计 MCP in LangChain

Install the necessary MCP adapters and initialize the server using the provided HTTP endpoint. Once connected, pass the tool list into your agent constructor to start making calls.

Yes, you can build a chain that triggers on a schedule to fetch `get_yesterday_overview`. Your agent then formats this into a summary and sends it wherever you need.

It does if you use the session context. By maintaining state, your agent remembers which site IDs were retrieved from `list_sites` across multiple turns.

The server responds as fast as the upstream API allows. You can track exact execution time for every tool call using standard framework tracing.

This server only touches traffic and site metadata, never your raw user credentials. Your data stays within the encrypted transport tunnel between the client and the Vinkius host.

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