MCP Scholarly
Enables users to search for academic articles on platforms like arXiv using specific keywords, with plans to integrate more scholarly databases in the future.
What is MCP Scholarly?
MCP Scholarly is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to enables users to search for academic articles on platforms like arxiv using specific keywords, with plans to integrate more scholarly databases in the future.
Enables users to search for academic articles on platforms like arXiv using specific keywords, with plans to integrate more scholarly databases in the future.
This server falls under the Search & Data Extraction category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- Enables users to search for academic articles on platforms l
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx mcp-scholarly-serverConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use MCP Scholarly
MCP Scholarly is a lightweight MCP server that gives AI models the ability to search arXiv for academic papers using keyword queries. It wraps the arXiv search API into a single search-arxiv tool, returning paper titles, authors, abstracts, and links — making it easy for researchers and students to discover relevant literature through natural language without leaving their AI assistant. The project plans to integrate additional scholarly databases in future releases.
Prerequisites
- Python 3.10 or later installed
- uv or uvx package manager installed (recommended), or Docker
- An MCP-compatible client such as Claude Desktop or Claude Code
- No API keys required — uses the public arXiv search API
Install via uvx (recommended)
Run mcp-scholarly directly with uvx. No virtual environment setup is required.
uvx mcp-scholarlyAlternatively run via Docker
If you prefer a containerized setup, pull and run the Docker image.
docker run --rm -i mcp/scholarlyAdd to your Claude Desktop config
Edit claude_desktop_config.json to register the scholarly server using uvx.
{
"mcpServers": {
"mcp-scholarly": {
"command": "uvx",
"args": ["mcp-scholarly"]
}
}
}Restart your MCP client
Restart Claude Desktop or reload Claude Code to pick up the new server.
Search for academic papers
The server exposes a single tool, search-arxiv, which accepts a keyword string and returns matching papers from arXiv. Ask Claude to find papers on any research topic.
MCP Scholarly Examples
Client configuration
Register mcp-scholarly using uvx in Claude Desktop. No environment variables or API keys are required.
{
"mcpServers": {
"mcp-scholarly": {
"command": "uvx",
"args": ["mcp-scholarly"]
}
}
}Prompts to try
Search arXiv for academic papers using natural language keyword queries.
- "Search arXiv for recent papers on retrieval-augmented generation"
- "Find academic articles about transformer attention mechanisms"
- "Look up papers on formal verification of neural networks"
- "Search for research on diffusion models for image generation"
- "Find papers about large language model alignment and safety"Troubleshooting MCP Scholarly
search-arxiv returns no results for a valid topic
arXiv search is keyword-sensitive. Try shorter, more specific terms (e.g., 'RAG retrieval' instead of 'how does RAG work'). The tool passes your query directly to the arXiv search API.
Server fails to start with uvx
Ensure uv is installed (curl -LsSf https://astral.sh/uv/install.sh | sh) and that your Python version is 3.10 or higher. As a fallback, use Docker: docker run --rm -i mcp/scholarly.
Results are outdated or missing recent papers
arXiv indexing can lag by a day or two for very new submissions. If you need papers from the past 24 hours, search directly on arxiv.org and paste the abstract URL for Claude to analyze.
Frequently Asked Questions about MCP Scholarly
What is MCP Scholarly?
MCP Scholarly is a Model Context Protocol (MCP) server that enables users to search for academic articles on platforms like arxiv using specific keywords, with plans to integrate more scholarly databases in the future. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install MCP Scholarly?
Follow the installation instructions on the MCP Scholarly GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with MCP Scholarly?
MCP Scholarly works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is MCP Scholarly free to use?
Yes, MCP Scholarly 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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Browse More Search & Data Extraction MCP Servers
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Set Up MCP Scholarly in Your Editor
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Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
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