Let AI assistants search, analyze, and explore academic papers from arXiv autonomously. Research Papers MCP bridges the gap between AI agents and academic research, enabling intelligent literature reviews, trend analysis, and paper discovery—all through natural language commands.
Everything you need to integrate arXiv research workflows with AI assistants and automation tools.
AI agents can independently search papers, analyze literature, and iterate on research questions without human intervention.
From paper discovery to bibliography export—manage the entire academic research lifecycle through AI commands.
Advanced field-specific queries with real-time arXiv access deliver blazing fast paper discovery for rapid research cycles.
Generate literature reviews, identify research gaps, and analyze trends with comprehensive AI-powered insights.
Extract citations, track paper versions, and discover related research with automated paper relationship mapping.
Works with Cursor, Claude Desktop, VS Code, and any MCP-compatible client for maximum flexibility.
No installation required - just configure your MCP client
{
"mcpServers": {
"ResearchPapersMCP": {
"command": "npx",
"args": ["-y", "research-papers-mcp@latest"]
}
}
}
npm install -g research-papers-mcp
{
"mcpServers": {
"ResearchPapersMCP": {
"command": "node",
"args": ["research-papers-mcp"]
}
}
}
git clone https://github.com/Saidiibrahim/search_papers
cd search_papers && npm install
{
"mcpServers": {
"ResearchPapersMCP": {
"command": "node",
"args": ["path/to/search_papers/dist/index.js"]
}
}
}
See Research Papers MCP in action
Contribute to make this tool even better
Submit pull requests, fix bugs, or add new features to enhance the research capabilities
View IssuesLearn how to set up your development environment and contribute to the project
Read GuideHave ideas for new tools or improvements? We'd love to hear your suggestions
Start Discussion