Retrieve detailed information about a specific paper by providing its arXiv ID using Hugging Face MCP Server. Streamline access to research data and metadata for efficient academic workflows.
Retrieve detailed statistics for a Hugging Face dataset, including config and split information, to analyze and understand dataset structure and content.
Retrieve comprehensive details about Hugging Face datasets, including descriptions, features, splits, and statistics. Validate dataset accessibility before fetching information.
An unofficial MCP server that provides semantic search capabilities for Hugging Face models and datasets, enabling Claude and other MCP-compatible clients to search, discover, and explore the Hugging Face ecosystem using natural language queries.
Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.