"Hugging Face" matching MCP servers:

A Model Context Protocol server that provides Claude and other LLMs with read-only access to Hugging Face Hub APIs, enabling interaction with models, datasets, spaces, papers, and collections through natural language.

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.

An MCP server that provides Hugging Face Hub API and Search endpoints through multiple transport protocols (STDIO, SSE, StreamableHTTP, and StreamableHTTPJson), enabling integration with AI model capabilities.

Enables access to 200,000+ machine learning models through the Hugging Face Inference API. Supports text generation, image creation, classification, translation, speech processing, embeddings, and more AI tasks.

Enables access to the Hugging Face Hub API to search and retrieve information about machine learning models, datasets, and their metadata. Provides comprehensive tools for exploring the Hugging Face ecosystem including model details, dataset information, and parquet file access.

A production-ready local MCP server for Agent Studio, providing tools for calculation, search, chat, and Hugging Face text generation via the Inference API.

Enables interaction with the Hugging Face Dataset Viewer API, allowing users to browse, search, filter, and analyze datasets hosted on the Hugging Face Hub.

Enables face detection and recognition in Agentic AI workflows using Azure Face API, supporting attribute detection, image comparison, and face recognition.

Enables MCP-capable assistants to quantize Hugging Face models into GGUF format and publish the results to your Hugging Face profile, with tools for credits, pricing, model browsing, and job status.

AgentAvow scans any MCP server, package (npm/PyPI/crates/Docker/Hugging Face), or GitHub repo and returns a signed, offline-recomputable 0–100 trust score with a plain safe / needs-review verdict. Authless and read-only, no account.

Enables AI agents to search, compare, and right-size Hugging Face models, including estimating whether a model fits in available GPU VRAM before downloading it.

Enables MCP-compatible AI agents to run structured searches over India's court judgments, tribunal matters, and legislation directly from Hugging Face parquet files, with automatic license attribution.

Provides access to over 100 curated AI agent skills from organizations like Anthropic, Vercel, and Hugging Face. It enables AI assistants to perform specialized tasks including document processing, security analysis, and web development through a standardized interface.

Tell your AI agent what you want a model to do. It searches Hugging Face for each part of the job and tells you which parts already exist there: which are an exact fit, which to fine-tune, which to train, and which are just code. Every model it names is real, current, and sized for your hardware.

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

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

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.