scholar-search-mcp 0.1.0

Model Context Protocol server for Semantic Scholar API

Scholar Search MCP

A Model Context Protocol (MCP) server that integrates the Semantic Scholar API so AI assistants (e.g. Claude, Cursor) can search and fetch academic paper metadata.

Features

• Search papers – Keyword search with optional year and venue filters
• Paper details – Full metadata (title, authors, abstract, citations, etc.)
• Citations & references – Papers that cite or are cited by a given paper
• Author info – Author profile and paper list
• Batch lookup – Fetch up to 500 papers in one call
• Recommendations – Similar papers for a given paper

Installation

pip install scholar-search-mcp

Configuration

Claude Desktop

Edit the config file:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

Add:

{
  "mcpServers": {
    "scholar-search": {
      "command": "python",
      "args": ["-m", "scholar_search_mcp"],
      "env": {
        "SEMANTIC_SCHOLAR_API_KEY": "your-api-key-here"
      }
    }
  }
}

Cursor

Add an MCP server in Cursor settings with the same command, args, and env as above.

API key (optional)

The Semantic Scholar API works without a key with lower limits. For higher limits:

1. Get an API key from Semantic Scholar API
2. Set SEMANTIC_SCHOLAR_API_KEY in the server env as shown above.

Tools

Tool	Description
search_papers	Search by query; optional limit, fields, year, venue
get_paper_details	Get one paper by ID (DOI, ArXiv ID, S2 ID, or URL)
get_paper_citations	Papers that cite the given paper
get_paper_references	References of the given paper
get_author_info	Author profile by ID
get_author_papers	Papers by author
get_paper_recommendations	Similar papers for a given paper
batch_get_papers	Details for up to 500 paper IDs

Testing with MCP Inspector

npm install -g @modelcontextprotocol/inspector
mcp-inspector python -m scholar_search_mcp

License

MIT

Links

• Semantic Scholar API
• Model Context Protocol
• MCP Python SDK