Turns arXiv and LaTeX mathematical papers into theorem dependency graphs, exposing MCP tools to load papers, list theorems, get theorem details, find dependencies, and locate where theorems are used.
Enables AI assistants to search, download, and read arXiv papers, with automatic detection of open-source code repositories and support for both LaTeX and PDF content.
Enables LLMs to search arXiv, extract and analyze paper content, and build a personal semantically-searchable research library with saved papers and notes.
Enables LLMs to search, download, and read arXiv papers with automatic PDF text extraction and section filtering. Provides AI assistants direct access to scientific literature with local caching for fast re-access.
Enables LLM agents to search arXiv, download papers, parse PDFs into structured sections, and extract key findings using client-side LLMs. Features persistent caching and layout-aware PDF extraction.
Enables AI agents to read, write, and compile LaTeX projects locally, view PDF pages as images, and manage project files, with live updates reflected in a web-based editor.