What is the Google Scholar MCP Server?

The Google Scholar MCP Server is a tool that allows AI assistants to search and access papers from Google Scholar programmatically using the Model Context Protocol (MCP).

How do I install the Google Scholar MCP Server?

You can install it manually by cloning the repository and installing the dependencies or automatically via Smithery using the provided commands for Claude, Cursor, Windsurf, and CLine.

What are the core features of the Google Scholar MCP Server?

The core features include paper search (keyword and advanced), efficient retrieval of metadata, access to author information, and support for academic research.

What MCP tools are available in the Google Scholar MCP Server?

The available MCP tools are search_google_scholar_key_words, search_google_scholar_advanced, and get_author_info.

What dependencies are required to run the Google Scholar MCP Server?

The dependencies include Python 3.10+, mcp[cli]>=1.4.1, scholarly>=1.7.0, and asyncio>=3.4.3. You can install them using pip install -r requirements.txt.

How can I use the Google Scholar MCP Server with Claude Desktop?

Add the provided configuration to your claude_desktop_config.json file. Make sure to adjust the paths to your Python executable and the server script.

What is MCP?

MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs, allowing AI models to interact with external data sources and tools.

What is UBOS?

UBOS is a full-stack AI Agent Development Platform focused on bringing AI Agents to every business department, helping you orchestrate AI Agents, connect them with enterprise data, build custom AI Agents with your LLM model and Multi-Agent Systems.