Scholar Search
An MCP server for academic paper search that integrates with AI assistants (e.g., Claude Code, Cursor), enabling them to search and retrieve academic paper metadata.
What is Scholar Search?
Scholar Search is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to mcp server for academic paper search that integrates with ai assistants (e.g., claude code, cursor), enabling them to search and retrieve academic paper metadata.
An MCP server for academic paper search that integrates with AI assistants (e.g., Claude Code, Cursor), enabling them to search and retrieve academic paper metadata.
This server falls under the Search & Data Extraction category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- An MCP server for academic paper search that integrates with
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx scholar-searchConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Scholar Search
Scholar Search MCP connects your AI assistant to academic databases — Semantic Scholar and arXiv — so you can search, retrieve, and analyze research papers without leaving your workflow. It exposes nine tools covering everything from basic paper search to citation network traversal, author profiles, and bulk batch retrieval of up to 500 records at once. No API key is required to get started since arXiv is fully open; an optional Semantic Scholar key unlocks higher rate limits for power users doing large literature reviews.
Prerequisites
- Python 3.10 or higher installed
- pip package manager available
- An MCP-compatible client (Claude Desktop, Cursor, or Claude Code)
- Optional: a free Semantic Scholar API key from semanticscholar.org for higher rate limits
Install the package
Install scholar-search-mcp from PyPI using pip. This pulls in all dependencies including the arXiv and Semantic Scholar client libraries.
pip install scholar-search-mcpVerify the installation
Confirm the module can be imported and the MCP server starts correctly before wiring it into your client.
python -m scholar_search_mcp --helpObtain an optional Semantic Scholar API key
Visit https://www.semanticscholar.org/product/api to sign up for a free API key. This is optional but removes the default rate limit of 100 requests per 5 minutes and is recommended for batch workflows.
Add the server to your MCP client configuration
Open your Claude Desktop config file (~/Library/Application Support/Claude/claude_desktop_config.json on macOS or %APPDATA%\Claude\claude_desktop_config.json on Windows) and add the scholar-search entry. Set environment variables to control which sources are enabled and optionally supply your API key.
{
"mcpServers": {
"scholar-search": {
"command": "python",
"args": ["-m", "scholar_search_mcp"],
"env": {
"SCHOLAR_SEARCH_ENABLE_SEMANTIC_SCHOLAR": "true",
"SCHOLAR_SEARCH_ENABLE_ARXIV": "true",
"SEMANTIC_SCHOLAR_API_KEY": "your_key_here"
}
}
}
}Restart your MCP client and verify connection
Restart Claude Desktop or your MCP client. The scholar-search tools (search_papers, get_paper_details, etc.) should appear in the available tool list. Try a simple paper search to confirm everything is working.
Scholar Search Examples
Client configuration
Full Claude Desktop configuration block for the Scholar Search MCP server with both sources enabled.
{
"mcpServers": {
"scholar-search": {
"command": "python",
"args": ["-m", "scholar_search_mcp"],
"env": {
"SCHOLAR_SEARCH_ENABLE_SEMANTIC_SCHOLAR": "true",
"SCHOLAR_SEARCH_ENABLE_ARXIV": "true",
"SEMANTIC_SCHOLAR_API_KEY": "your_optional_key_here",
"SCHOLAR_SEARCH_CACHE_TTL_SECONDS": "86400"
}
}
}
}Prompts to try
Example prompts that exercise the server's nine research tools across common academic workflows.
- "Search for recent papers on large language model hallucination from 2023 onwards"
- "Get full details for arXiv paper 2305.10601 including abstract and citation count"
- "Who has cited the paper with DOI 10.1145/3442381.3449899?"
- "Find all papers by Yoshua Bengio published after 2020"
- "Get recommendations for papers similar to arXiv:2303.08774"
- "Batch fetch metadata for these 10 arXiv IDs and summarize their methods sections"Troubleshooting Scholar Search
Rate limit errors from Semantic Scholar even with an API key
Ensure SEMANTIC_SCHOLAR_API_KEY is set correctly in the env block of your config. Keys must be passed as environment variables, not as CLI arguments. Verify the key is active at semanticscholar.org/product/api.
Module not found error when starting the server
Make sure you installed into the same Python environment your MCP client uses. If using a virtual environment, specify the full Python path in the command field: "/path/to/venv/bin/python" instead of "python".
arXiv searches return no results for recent papers
arXiv indexing can lag by a day or two. Try broadening your date range or using Semantic Scholar as the primary source by setting SCHOLAR_SEARCH_ENABLE_SEMANTIC_SCHOLAR to true.
Frequently Asked Questions about Scholar Search
What is Scholar Search?
Scholar Search is a Model Context Protocol (MCP) server that mcp server for academic paper search that integrates with ai assistants (e.g., claude code, cursor), enabling them to search and retrieve academic paper metadata. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Scholar Search?
Follow the installation instructions on the Scholar Search GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Scholar Search?
Scholar Search works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Scholar Search free to use?
Yes, Scholar Search is open source and available under the MIT License license. You can use it freely in both personal and commercial projects.
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