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Baidu Search MCP Server

Baidu Search MCP Server

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github.com/EvilranSearch28Updated 52w ago

About Baidu Search MCP Server

An MCP server that provides web search through Baidu and can fetch and parse page content. Its output is formatted for large language model use, and both search and fetching include built-in rate limiting.

Key features

  1. 01Web search through Baidu
  2. 02Webpage fetching with text extraction
  3. 03Built-in rate limits for search and fetching
  4. 04Cleans Baidu redirect URLs and removes ads
  5. 05Error handling with logging through MCP context

Use cases

  1. 01Letting Claude Desktop search Chinese-language web content
  2. 02Retrieving the body text of pages from search results
  3. 03Supplying LLMs with cleaned Chinese search results

MCP support

This project is an MCP server that exposes two tools to MCP clients: search for Baidu queries and fetch_content for retrieving webpage text.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"baidu": {
"command": "npx",
"args": [
"-y",
"@smithery/cli"
]
}
}
}
Run commandnpx -y @smithery/cli

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npm@smithery/cli

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

MseeP.ai Security Assessment Badge

Baidu Search MCP Server

smithery badge

A Model Context Protocol (MCP) server that provides web search capabilities through Baidu, with additional features for content fetching and parsing.

Baidu Server MCP server

Features

  • Web Search: Search Baidu with advanced rate limiting and result formatting
  • Content Fetching: Retrieve and parse webpage content with intelligent text extraction
  • Rate Limiting: Built-in protection against rate limits for both search and content fetching
  • Error Handling: Comprehensive error handling and logging
  • LLM-Friendly Output: Results formatted specifically for large language model consumption

Installation

Installing via Smithery

To install Baidu Search Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @Evilran/baidu-mcp-server --client claude
Installing via uv

Install directly from PyPI using uv:

uv pip install baidu-mcp-server

Usage

Running with Claude Desktop
  1. Download Claude Desktop
  2. Create or edit your Claude Desktop configuration:
    • On macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
    • On Windows: %APPDATA%\Claude\claude_desktop_config.json

Add the following configuration:

{
    "mcpServers": {
        "baidu-search": {
            "command": "uvx",
            "args": ["baidu-mcp-server"]
        }
    }
}
  1. Restart Claude Desktop
Development

For local development, you can use the MCP CLI:

# Run with the MCP Inspector
mcp dev server.py

# Install locally for testing with Claude Desktop
mcp install server.py

Available Tools

1. Search Tool
async def search(query: str, max_results: int = 10) -> str

Performs a web search on Baidu and returns formatted results.

Parameters:

  • query: Search query string
  • max_results: Maximum number of results to return (default: 10)

Returns: Formatted string containing search results with titles, URLs, and snippets.

2. Content Fetching Tool
async def fetch_content(url: str) -> str

Fetches and parses content from a webpage.

Parameters:

  • url: The webpage URL to fetch content from

Returns: Cleaned and formatted text content from the webpage.

Features in Detail

Rate Limiting
  • Search: Limited to 30 requests per minute
  • Content Fetching: Limited to 20 requests per minute
  • Automatic queue management and wait times
Result Processing
  • Removes ads and irrelevant content
  • Cleans up Baidu redirect URLs
  • Formats results for optimal LLM consumption
  • Truncates long content appropriately
Error Handling
  • Comprehensive error catching and reporting
  • Detailed logging through MCP context
  • Graceful degradation on rate limits or timeouts

Contributing

Issues and pull requests are welcome! Some areas for potential improvement:

  • Additional search parameters (region, language, etc.)
  • Enhanced content parsing options
  • Caching layer for frequently accessed content
  • Additional rate limiting strategies

License

This project is licensed under the MIT License.

Acknowledgments

The code in this project references the following repositories:

Thanks to the authors and contributors of these repositories for their efforts and contributions to the open-source community.

Comments

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