"Hugging Face" matching MCP servers:

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 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.

Enables generating game assets — images, 3D meshes, sound and music — through free Hugging Face Spaces with no GPU or subscription, plus procedural synthesizers that consume no quota at all. Adds licence gating, per-take provenance metadata, and post-processing such as audio trimming/looping/normalising and six-angle Blender mesh renders.

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.

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.

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.

Checks whether an open-weight LLM fits your GPU: VRAM for weights, KV cache and overhead at each quantisation, a tokens-per-second ceiling, the longest context that fits, and what would work instead when it doesn't. Reads any Hugging Face repo's config.json. Free, read-only, no API key.

A complete MCP server for Retrieval-Augmented Generation with file management and vector memory for agents. Supports multiple document formats (PDF, DOCX, TXT, MD, CSV, JSON) with semantic search using Hugging Face embeddings and ChromaDB for efficient vector storage.

Gives Claude Code, Cursor and other agents structural awareness of a PyTorch model: layers, params, FLOPs, blast radius, the design linter, a full readiness/cost/deployment verdict, and a ranker for which of k candidate designs to train. Reads a .py, a .neurarch.json, 81 bundled reference architectures, or a Hugging Face repo. Offline, no API key.

Provides tools for greetings, calculations, weather, geocoding, and image generation via Hugging Face, deployable to Vercel and integrable with Cursor.

Provides multilingual greetings in English, Korean, and Japanese, and generates AI images using the FLUX.1-schnell model from Hugging Face.

A boilerplate for building and deploying MCP servers on Vercel, featuring example tools like greeting, calculator, weather, and Hugging Face image generation.

Enables safety-ranked discovery of open-source components across npm, PyPI, crates.io, RubyGems, GitHub, and Hugging Face, with license, security, and health checks.

Search and retrieve models, datasets, and spaces from Hugging Face Hub. Enables browsing trending items and getting detailed info on repos.

Connects LLMs to the Hugging Face Hub and thousands of Gradio AI applications, enabling repository search, file access, Space interaction, jobs, and sandbox tools through MCP. Supports STDIO and Streamable HTTP transports with optional Hugging Face authentication.

A boilerplate project for quickly developing Model Context Protocol (MCP) servers using TypeScript SDK, featuring example tools (calculator, greet), resources (server info), and AI image generation capabilities via Hugging Face.

Enables ChatGPT, Claude and Gemini to run read-only lookups across EMS protocol guides, judges and courts, public health data (NPI registry, drug labels, recalls, adverse events), and open-source model sizing with VRAM estimates and Hugging Face search. Connects over Streamable HTTP with OAuth 2.1 or API keys, offering anonymous, free-key and paid Pro call quotas.