"Hugging Face" matching MCP servers:

Enables LLMs to search and retrieve read-only information from the Hugging Face Hub about models, datasets, Spaces, papers, and collections. It also supports model comparison and paper summarization prompts.

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

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.

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.

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.

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.

Enables AI assistants to fetch sourced, citable face measurement percentiles, face type definitions and threshold rules, methodology and citation details, and to classify a face shape from four distances using the site's seven rules in order. Read-only and takes no photo.

MCP server for the abliteration.org catalog: 18 read-only tools over every abliterated and uncensored LLM on Hugging Face, with method classification, download trends, deletion history, and four alignment indices.

Enables plain-English description of training data needs to search Hugging Face and GitHub, composing coverage-scored training packs without API keys or Bridge.

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.

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 autonomous agents to cross-reference factual claims against multiple source documents, detect ungrounded or hallucinated statements, and return normalized confidence scores via the verify_claim tool.

Enables AI agents to look up any US House district or Senate race and get the incumbent, every FEC-registered candidate by party with receipts, disbursements and cash on hand, plus inferred primary winners and the primary, runoff and general election dates. A companion tool lists the races in a state so you can find the right district.

Finds new AI model, product and repository names on X, Hugging Face, GitHub and sitemaps, plus sites that just added a payment link, then sizes their keywords with search volume, Google Trends and page-one competition.