Database · MODEL CONTEXT PROTOCOL
Evilran baidu mcp server
Baidu Search MCP Server I A Model Context Protocol (MCP) server that provides web search capabilities through Baidu, with additional features for content fetching and parsing.
连接能力
Evilran baidu mcp server 为 AI Agent 提供什么
- **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
- Download [Claude Desktop](https://claude.ai/download)
- 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`
- Restart Claude Desktop
- `query`: Search query string
- `max_results`: Maximum number of results to return (default: 10)
- `url`: The webpage URL to fetch content from
- Search: Limited to 30 requests per minute
- Content Fetching: Limited to 20 requests per minute
- Automatic queue management and wait times
- Removes ads and irrelevant content
- Cleans up Baidu redirect URLs
- Formats results for optimal LLM consumption
- Truncates long content appropriately
- Comprehensive error catching and reporting
- Detailed logging through MCP context
- Graceful degradation on rate limits or timeouts
- Additional search parameters (region, language, etc.)
- Enhanced content parsing options
- Caching layer for frequently accessed content
- Additional rate limiting strategies
- [nickclyde/duckduckgo-mcp-server](https://github.com/nickclyde/duckduckgo-mcp-server)
- [BaiduSpider/BaiduSpider](https://github.com/BaiduSpider/BaiduSpider)
安全
MCP 收录不等于安全审核
MCP 服务器可能获得模型上下文、凭据、本地文件或调用外部系统的权限。连接 Agent 前,请检查代码、环境变量、网络行为、软件包来源与维护状态。
README
仓库文档
A Model Context Protocol (MCP) server that provides web search capabilities through Baidu, with additional features for content fetching and parsing.
- 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
To install Baidu Search Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @Evilran/baidu-mcp-server --client claudeInstall directly from PyPI using uv:
uv pip install baidu-mcp-server- 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
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.pyasync def search(query: str, max_results: int = 10) -> strPerforms 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.
async def fetch_content(url: str) -> strFetches and parses content from a webpage.
Parameters:
url: The webpage URL to fetch content from
Returns: Cleaned and formatted text content from the webpage.
- Search: Limited to 30 requests per minute
- Content Fetching: Limited to 20 requests per minute
- Automatic queue management and wait times
- Removes ads and irrelevant content
- Cleans up Baidu redirect URLs
- Formats results for optimal LLM consumption
- Truncates long content appropriately
- Comprehensive error catching and reporting
- Detailed logging through MCP context
- Graceful degradation on rate limits or timeouts
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
This project is licensed under the MIT License.
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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