google-scholar-search-mcp
An MCP server for searching Google Scholar, enabling paper search, author lookup, citation tracking, and BibTeX export for AI assistants and automation workflows.
README
google-scholar-search-mcp
An MCP (Model Context Protocol) server for searching Google Scholar, built for AI assistants and automation workflows that need papers, authors, citations, and BibTeX entries.
Table of Contents
Features
- Paper Search: Query Google Scholar by keyword with filtering, sorting, and pagination
- Author Lookup: Find researcher profiles with publication lists and h-index metrics
- Citation Tracking: Retrieve papers that cite a given work
- Paper Details: Get full metadata, citations-per-year graphs, and public access info
- BibTeX Export: Generate citation entries in BibTeX format
- Bulk Search: Batch search multiple queries with automatic rate limiting
- Rate Limiting: Built-in delays between requests to avoid being blocked
- Proxy Support: Optional proxy configuration (free, single, or ScraperAPI)
Installation
Requirements
Python 3.11or later- Dependencies:
mcp[cli]>=1.4.0,scholarly>=1.7.11,pydantic>=2.0(see pyproject.toml)- project uses
uvfor dependency management
- project uses
Install it from PyPI
pip install google-scholar-search-mcp
Build from Source
git clone https://github.com/LWaetzig/google-scholar-search-mcp.git
cd google-scholar-search-mcp
pip install -e .
Note: This server uses the scholarly library to access Google Scholar. Respect Google's Terms of Service and use rate limiting appropriately to avoid being blocked.
Configuration
Configure the MCP server via environment variables:
| Variable | Default | Description |
|---|---|---|
GS_MIN_DELAY |
5.0 |
Minimum seconds between requests |
GS_MAX_DELAY |
15.0 |
Maximum seconds between requests |
GS_MAX_RETRIES |
3 |
Number of retries on failure |
GS_PROXY_TYPE |
none |
Proxy mode: none, free, single, scraperapi |
GS_PROXY_HTTP |
— | HTTP proxy URL (for single mode) |
GS_PROXY_HTTPS |
— | HTTPS proxy URL (for single mode) |
GS_SCRAPERAPI_KEY |
— | ScraperAPI key (for scraperapi mode) |
GS_TIMEOUT |
30 |
Request timeout in seconds |
Proxy Configuration Examples
No Proxy (Default)
export GS_PROXY_TYPE=none
Free Proxy
export GS_PROXY_TYPE=free
Single Proxy
export GS_PROXY_TYPE=single
export GS_PROXY_HTTP=http://proxy.example.com:8080
export GS_PROXY_HTTPS=https://proxy.example.com:8080
ScraperAPI
export GS_PROXY_TYPE=scraperapi
export GS_SCRAPERAPI_KEY=your_key_here
Usage
Detailed documentation about single tools can be found here
Integration with Claude Desktop
Add the server to your Claude Desktop configuration:
| Platform | Path |
|---|---|
| macOS | ~/Library/Application Support/Claude/claude_desktop_config.json |
| Windows | %APPDATA%\Claude\claude_desktop_config.json |
Add the google_scholar_mcp entry under mcpServers, replacing the path with the absolute path to your clone:
{
"mcpServers": {
"google-scholar": {
"command": "python",
"args": ["-m", "google_scholar_mcp.server"],
"env": {
"GS_MIN_DELAY": "5.0",
"GS_MAX_DELAY": "15.0",
"GS_PROXY_TYPE": "none"
}
}
}
}
After updating the config, restart Claude Desktop. The Google Scholar tools will appear in the MCP Tools panel.
Integration with Other MCP Clients
Any MCP client (e.g., Cline, Continue, or custom tools) can use this server. Configure the connection to:
Command: python -m google_scholar_mcp.server
Transport: stdio
Rate Limiting
The server automatically enforces rate limiting between requests to avoid overloading Google Scholar's servers:
- Min Delay (default 5s): Minimum wait between consecutive requests
- Max Delay (default 15s): Maximum wait (randomized to avoid patterns)
- Max Retries (default 3): Retry failed requests up to this many times
These settings help prevent being blocked by Google Scholar. Adjust via environment variables if needed:
export GS_MIN_DELAY=3.0
export GS_MAX_DELAY=10.0
export GS_MAX_RETRIES=5
⚠️ IP Blocking Warning
If you exceed Google Scholar's rate limits despite the rate limiter:
- Your IP may be temporarily blocked (usually 24-48 hours)
- All requests will fail with connection errors or 429 responses
- Blocked IPs cannot make requests even with valid proxies on the same IP range
- Repeated violations may trigger permanent blocks or require CAPTCHA solving
Recommended Practices:
- Never decrease delays below 5 seconds — the defaults are tuned for reliability
- Use the bulk_search tool instead of rapid sequential searches — it includes built-in delays
- Add extra buffer during bulk operations — consider setting
GS_MIN_DELAY=10.0for large jobs - Use a proxy service (free proxy or ScraperAPI) to distribute requests across multiple IPs
- Monitor for 429 errors — if you see them, increase delays immediately and wait before retrying
- Spread requests over time — don't run 100 queries in 5 minutes, even with delays
Recovery from IP Blocks
If your IP gets blocked:
- Wait 24-48 hours for the temporary block to expire
- Use a proxy — enable
GS_PROXY_TYPE=freeorscraperapito route through different IPs - Change your network — use a different WiFi/ISP temporarily if possible
- Contact support — for persistent blocks, escalate to Google Scholar support
Choosing Appropriate Delays
| Scenario | GS_MIN_DELAY | GS_MAX_DELAY | Notes |
|---|---|---|---|
| Single searches | 5.0 | 15.0 | Default; safe for occasional queries |
| Bulk operations | 10.0 | 20.0 | Use for batch jobs; prevents rapid-fire requests |
| Heavy load | 15.0 | 30.0 | Use with proxy for large-scale research |
| Aggressive ⚠️ | <5.0 | <10.0 | Not recommended; high risk of IP blocking |
Troubleshooting
"Error: 429 Too Many Requests"
You've hit Google Scholar's rate limit. Solutions:
- Increase delays: Set higher
GS_MIN_DELAYandGS_MAX_DELAY - Use a proxy: Set
GS_PROXY_TYPE=freeor use ScraperAPI - Wait and retry: Google Scholar may be temporarily blocking; try again later
"No results found"
- Check your query syntax (Google Scholar supports advanced search operators)
- Ensure the author/paper name is spelled correctly
- Try a simpler query with fewer keywords
"Connection timeout"
- Increase
GS_TIMEOUTif your network is slow - Check your internet connection
- Verify proxy settings if using a proxy
Contributing
Contributions are welcome! Please:
- Fork the repository
- Create a feature branch (
git checkout -b feature/your-feature) - Commit your changes with clear messages
- Push to your fork
- Open a pull request
Support
For issues, questions, or feature requests, please open an issue on GitHub.
License
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。
mcp-server-qdrant
这个仓库展示了如何为向量搜索引擎 Qdrant 创建一个 MCP (Managed Control Plane) 服务器的示例。