"Hugging Face" matching MCP servers:

Enables searching and gathering information from multiple online sources (web, Twitter/X, Telegram, GitHub, Hugging Face, arXiv) through a unified MCP interface.

MCP server that brings AI paper reading and code repository discovery from Hugging Face Papers into any MCP-compatible client.

Enables assistants to search, fetch daily curated lists, retrieve metadata, and generate citations for Hugging Face papers.

An MCP server for the Hugging Face Dataset Viewer API that enables searching, fetching, and filtering datasets on the Hugging Face Hub. It allows users to explore schemas, perform full-text searches, and analyze dataset statistics through natural language.

Typed MCP server for Hugging Face LeRobot workflows. Provides a structured, auditable interface for LeRobot CLI, examples, datasets, and dataset conversion.

Unified MCP server for discovering open datasets across Hugging Face, Zenodo, and Kaggle, with ranked search results and one-click Colab starter code generation.

Enables searching, fetching, and analyzing scientific papers from ArXiv, ACL Anthology, Semantic Scholar, and Hugging Face datasets, with optional LLM-powered document QA and research proposal workflows.

Provides direct access to the Hugging Face Hub for searching models and datasets, fetching metadata, and running inference on text, images, and audio.

An MCP server that tracks trending AI models, datasets, and spaces on Hugging Face.

A multi-MCP server hub that hosts several independent MCP servers (e.g., DuckDuckGo, Zhihu, Doubao, Academic) with per-path authentication, deployable on Hugging Face Spaces.

This MCP server enables users to interact with and analyze the dair-ai/emotion dataset from Hugging Face containing labeled Twitter messages. It provides tools to sample data, search text, and perform statistical analysis on emotion distributions.

MCP Extension that gives LLMs access to arXiv and Hugging Face papers, enabling users to discuss papers, search for new research, and organize literature reviews through natural conversation.

Enables real-time tracking of AI/LLM research progress by searching and aggregating content from arXiv, GitHub, Hugging Face, and Papers with Code. Supports intelligent search, automated daily/weekly research summaries, and covers 15+ AI research areas with smart caching.

Enables reviewing and managing AI research paper candidates from arXiv, Semantic Scholar, and Hugging Face Daily Papers, scored against personal interests, via MCP tools in Claude Desktop or Cowork.

Verifies claims with verdicts (supported/disputed/unverifiable), confidence scores, and cited sources by cross-referencing FoundryNet Data Network and web search.

An MCP server that fetches live trends from X, Google News, GitHub, and Hugging Face, and generates a self-contained HTML dashboard displaying top 20 lists for AI news, coding repositories, and models.

Turns Claude into a race engineer for original Assetto Corsa by reading telemetry, storing laps, and providing engineer-grade summaries, alongside read/write access to car setups.

MCP server that provides F1 telemetry analysis, tyre degradation modeling, and pit strategy recommendations, delivering race engineer-style calls grounded in real data. It exposes tools for degradation fits, fuel correction, and strategy reasoning via LangGraph.

This MCP server enables AI agents to extract, verify, and cache factual claims from text using Claude Haiku and semantic fingerprinting, with tools for content verification, signal verification, and fact memory search.

Enables querying, summarizing, comparing ATPCO fare CSV snapshots and shopping live fares via engine-wrapper-service, all through MCP clients like Claude.