Enables AI assistants to search and access arXiv research papers through a simple Message Control Protocol interface, allowing for paper search, download, listing, and reading capabilities.
Provides RAG capabilities for semantic document search using Qdrant vector database and Ollama/OpenAI embeddings, allowing users to add, search, list, and delete documentation with metadata support.
Enables real-time search and retrieval of academic paper information from multiple sources, providing access to paper metadata, abstracts, and full-text content when available, with structured data responses for integration with AI models that support tool/function calling.
The ArXiv MCP Server bridges the gap between AI models and academic research by providing a sophisticated interface to arXiv's extensive research repository. This server enables AI assistants to perform precise paper searches and access full paper content, enhancing their ability to engage with scientific literature.