Paperclip is an open-source tool designed to help AI systems and developer tools access academic research papers through a standardized interface. The project implements a server based on the Model Context Protocol (MCP), a framework that allows large language models and AI agents to connect to external data sources and tools in a consistent way. By acting as a middleware layer, Paperclip aggregates multiple academic databases and exposes them through a single interface, allowing AI applications to search and retrieve scholarly papers without needing to integrate with each provider individually. The system supports repositories such as arXiv, OpenAlex, and the Open Science Framework, giving AI agents access to a large body of research literature. Instead of requiring separate APIs and authentication flows for each service, Paperclip provides unified search and retrieval capabilities that simplify integration into AI workflows.
Features
- Unified search interface for multiple academic paper repositories
- Model Context Protocol server designed for integration with AI agents
- Support for research sources such as arXiv, OpenAlex, and OSF
- Standardized API for retrieving paper metadata and content
- Compatibility with MCP clients such as AI assistants and developer tools
- Self-hosted deployment for custom research and automation workflows