About Baidu MCP Server
Baidu MCP Server is an MCP server published by Evilran in the Developer Tools category: 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.
The repository has 28 stars and 8 forks, with the last commit 12 months ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.
Install
git clone https://github.com/Evilran/baidu-mcp-serverThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
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Security checks
Static checks derived from the repository 5 days ago. Heuristics on the source, not an audit.
- ✓README presentThe repository ships documentation.
- ✓License declaredUsable under a stated license.
- !Tests presentNo tests found. Behaviour changes may go unnoticed between versions.
- ✓Dependencies pinnedA lockfile pins dependency versions.
- ✓No dynamic code executionSource scan found no eval, dynamic Function, or shell execution.
- !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.
Releases
README
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.
README fetched from the repository 5 days ago. The original is authoritative.
