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Google Scholar MCP Server

@shiwenbin1617

Repository

Basic information

Category

Other

Transports

stdio

Author

shiwenbin1617

About Google Scholar MCP Server

No overview available yet

Google Scholar MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "google-scholar-mcp-server-shiwenbin1617": {
      "command": "npx",
      "args": [
        "-y",
        "@smithery/cli@latest",
        "install",
        "@JackKuo666/google-scholar-mcp-server",
        "--client",
        "claude",
        "--config",
        "{}"
      ]
    }
  }
}

Google Scholar MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

Fetch the live tool list by running this server in a temporary sandbox using the button above.

Overview

What is Google Scholar MCP Server?

Google Scholar MCP Server bridges AI assistants and Google Scholar through the Model Context Protocol (MCP). It enables AI models to search for academic papers and access paper metadata, author information, and advanced search results programmatically.

How to use Google Scholar MCP Server?

Install Python 3.10+, dependencies (pip install -r requirements.txt), then run python google_scholar_server.py. The server exposes three MCP tools: search_google_scholar_key_words, search_google_scholar_advanced, and get_author_info. Add the server configuration to Claude Desktop, Cursor, Windsurf, or Cline MCP settings.

Key features of Google Scholar MCP Server

  • Search Google Scholar papers by keywords
  • Perform advanced searches with author and year filters
  • Retrieve detailed author information
  • Fast access to paper metadata
  • Easy integration with AI assistants via MCP
  • Supports Claude Desktop, Cursor, Windsurf, and Cline

Use cases of Google Scholar MCP Server

  • Academic literature reviews and research support
  • Building AI‑powered research assistants
  • Automating paper retrieval for data analysis
  • Enabling chatbots to answer questions about scholarly articles

Frequently asked questions

1

What does Google Scholar MCP Server do compared to alternatives?

It provides a programmatic MCP interface to Google Scholar, offering search, advanced search, and author lookup tools directly for AI assistants, without requiring a separate API key.

2

What are the runtime dependencies?

Python 3.10 or later, and packages `mcp[cli]`, `scholarly`, and `asyncio`. Install via `pip install -r requirements.txt`.

3

Where does the data come from and reside?

Data is fetched live from Google Scholar via web scraping using the `scholarly` library; no local storage is used.

4

What are the known limitations?

The server relies on web scraping and respects Google Scholar’s terms of service. The number of results per search can be limited by passing a `num_results` parameter (default 5). No authentication mechanism is provided.

5

How is the server transported and authenticated?

The server communicates over stdio (standard I/O) as a standard MCP server. No authentication or external transport configuration is required.

Comments

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