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

Q: Can LlamaIndex query Baidu Analytics / 百度统计 real-time data?

Yes, you can call getrealtimemetrics as part of your retrieval process. The agent fetches the latest figures and adds them to the context before generating an answer.

Index Baidu Analytics / 百度统计 data inside LlamaIndex for grounded, searchable insights.

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Connect Baidu Analytics / 百度统计 MCP to LlamaIndex

Create your Vinkius account to connect Baidu Analytics / 百度统计 to LlamaIndex 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 LlamaIndex

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Index Baidu Analytics / 百度统计 site stats

Turn raw traffic reports from `get_geo_distribution` into searchable knowledge. LlamaIndex ingests these results so you can query your historical site performance using natural language. Stop guessing about past traffic spikes. The agent searches the index to find exactly when and where your visitors originated.

Ground AI answers with Baidu Analytics / 百度统计

Build a RAG pipeline that pulls from `query_custom_metrics` to answer specific questions about your traffic. The model uses the actual API data as the source of truth, preventing hallucinations. Your agent gets the precise numbers it needs to write accurate reports. It treats the analytics platform as a live knowledge base.

Filter Baidu Analytics / 百度统计 data access

Use the allowed_tools filter to restrict which parts of the analytics platform your LlamaIndex agent can touch. You keep control over your data exposure while letting the agent perform its analysis. It’s a safe way to give your AI access to sensitive site metrics. You define the boundaries, and the agent stays within them.

Setup guide

Set up Baidu Analytics / 百度统计 MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Baidu Analytics / 百度统计 MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Baidu Analytics / 百度统计 tools.",
)
response = await agent.run("List recent Baidu Analytics / 百度统计 data")

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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 LlamaIndex

The MCP server tools provide the raw data, which LlamaIndex then processes into a vector store. This allows your agent to perform semantic searches over your site metrics.

Yes, you can call `get_realtime_metrics` as part of your retrieval process. The agent fetches the latest figures and adds them to the context before generating an answer.

You wrap the tools in a tool spec and pass them to your agent. It handles the mapping between the analytics API calls and your RAG logic.

Once you index the output of the tools, your search history becomes a queryable database. You can ask about traffic trends from months ago with ease.

Your visitor metrics are processed in memory and indexed locally. The connection to the server is authenticated via a single endpoint token, ensuring only your agent accesses the analytics stream.

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