How do I find my Baidu Analytics Token and Site ID?

Log in to the [Baidu Analytics Console](https://tongji.baidu.com/), navigate to [Management] -> [Site List] to find your numeric Site ID. The API Token is usually provided in the API settings or developer services section after account verification.

What metrics are supported in real-time queries?

Real-time tools provide access to Page Views (PV), Unique Visitors (UV), IP counts, and the current number of online users on your site.

Can I query data for specific dates?

Yes! Use the trend and metric tools with `start_date` and `end_date` in `YYYYMMDD` format. Your agent will retrieve the historical data for the requested period.

Baidu Analytics / 百度统计 MCP Server for Pydantic AI 8 tools — connect in under 2 minutes

Name: Baidu Analytics / 百度统计
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 8 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Baidu Analytics / 百度统计 through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Baidu Analytics / 百度统计 "
            "(8 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Baidu Analytics / 百度统计?"
    )
    print(result.data)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Baidu Analytics / 百度统计 MCP Server

Empower your AI agent to orchestrate your web analytics and visitor insights with Baidu Analytics (百度统计), the dominant traffic analysis platform in China. By connecting Baidu Analytics to your agent, you transform complex metric reporting, real-time visitor tracking, and source auditing into a natural conversation. Your agent can instantly retrieve site lists, query real-time PV/UV data, audit daily visitor trends, and generate custom performance reports without you ever needing to navigate the comprehensive Baidu Tongji Dashboard. Whether you are conducting a digital marketing audit or monitoring the performance of a new landing page, your agent acts as a real-time data coordinator, providing accurate results from a single, authorized source.

Pydantic AI validates every Baidu Analytics / 百度统计 tool response against typed schemas, catching data inconsistencies at build time. Connect 8 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Site Orchestration — List all registered sites and verify target Site ID configurations for precise data access.
Real-time Auditing — Retrieve immediate visitor metrics including Page Views (PV), Unique Visitors (UV), and online user counts.
Trend Analysis — Audit daily traffic trends and high-level performance summaries for specific date ranges.
Performance Auditing — Query page rankings, geographic distributions, and traffic source details.
Custom Reporting — Execute advanced queries on site data using flexible API methods and metrics.

The Baidu Analytics / 百度统计 MCP Server exposes 8 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Baidu Analytics / 百度统计 to Pydantic AI via MCP

Follow these steps to integrate the Baidu Analytics / 百度统计 MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 8 tools from Baidu Analytics / 百度统计 with type-safe schemas

Why Use Pydantic AI with the Baidu Analytics / 百度统计 MCP Server

Pydantic AI provides unique advantages when paired with Baidu Analytics / 百度统计 through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Baidu Analytics / 百度统计 integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Baidu Analytics / 百度统计 connection logic from agent behavior for testable, maintainable code

Baidu Analytics / 百度统计 + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Baidu Analytics / 百度统计 MCP Server delivers measurable value.

Type-safe data pipelines: query Baidu Analytics / 百度统计 with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Baidu Analytics / 百度统计 tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Baidu Analytics / 百度统计 and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Baidu Analytics / 百度统计 responses and write comprehensive agent tests

Baidu Analytics / 百度统计 MCP Tools for Pydantic AI (8)

These 8 tools become available when you connect Baidu Analytics / 百度统计 to Pydantic AI via MCP:

get_daily_trend

Get daily traffic trend

get_geo_distribution

Get visitor geographic data

get_page_rankings

Get top visited pages

get_realtime_metrics

Get real-time statistics

get_source_data

g., search, direct). Get visitor sources

get_yesterday_overview

Get yesterday traffic summary

list_sites

List all analytics sites

query_custom_metrics

Execute custom report query

Example Prompts for Baidu Analytics / 百度统计 in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Baidu Analytics / 百度统计 immediately.

"Check the real-time visitor stats for my site."

"Show me the visitor trend for the last 7 days."

"List all sites in my Baidu Analytics account."

Troubleshooting Baidu Analytics / 百度统计 MCP Server with Pydantic AI

Common issues when connecting Baidu Analytics / 百度统计 to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Baidu Analytics / 百度统计 + Pydantic AI FAQ

Common questions about integrating Baidu Analytics / 百度统计 MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Baidu Analytics / 百度统计 MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.