
Baidu Search
Enables web searches through Baidu's search engine, returning formatted search results with built-in rate limiting and error handling.
Provides web search capabilities through Baidu's search engine, enabling retrieval of search results and webpage content with robust error handling and content parsing.
What it does
- Search Baidu with customizable result limits
- Retrieve and parse webpage content
- Format search results for AI consumption
- Handle rate limiting automatically
Best for
About Baidu Search
Baidu Search is a community-built MCP server published by evilran that provides AI assistants with tools and capabilities via the Model Context Protocol. Baidu Search provides fast web search using baidu.com. Retrieve results and webpage content with robust error handling a It is categorized under search web. This server exposes 1 tool that AI clients can invoke during conversations and coding sessions.
How to install
You can install Baidu Search in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport. This server supports remote connections over HTTP, so no local installation is required.
License
Baidu Search is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Tools (1)
Search Baidu and return formatted results. Args: query: The search query string max_results: Maximum number of results to return (default: 6) deep_mode: Deep search the web content (default: False) ctx: MCP context for logging
Baidu Search MCP Server
A Model Context Protocol (MCP) server that provides web search capabilities through Baidu, with additional features for content fetching and parsing.
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
- Download Claude Desktop
- 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
- On macOS:
Add the following configuration:
{
"mcpServers": {
"baidu-search": {
"command": "uvx",
"args": ["baidu-mcp-server"]
}
}
}
- 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 stringmax_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.
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