"Hugging Face" matching MCP servers:

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

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.

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.

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.

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.

Provides various utilities including timezone-aware time queries, basic calculator operations, multilingual greetings, code review prompts, and AI image generation through Hugging Face API.

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.

Enables management of local video datasets with directory browsing and direct upload capabilities to Hugging Face Hub repositories. Supports video file validation, batch uploads, and automated dataset repository creation with secure authentication.

Provides AI agents with 6 tools for searching Hugging Face models, GitHub trending repos, analyzing GitHub repositories, fetching dev.to articles, Show HN launches, and Product Hunt daily launches. Built for dev tooling research and AI ecosystem analysis.

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

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 AI assistants to generate realistic, synthetic test data on demand, including valid PESELs, NIPs, addresses, and more across 27 EU countries, through two tools: list_generators and generate.

Stdio MCP Server wrapping custom Python runtime (LocalPythonExecutor) from Hugging Faces' smolagents framework. The runtime combines the ease of setup (compared to docker, VM, cloud runtimes) while providing safeguards and limiting operations/imports that are allowed inside the runtime.

Enables AI agents to execute server-side JavaScript and perform CRUD operations directly on ServiceNow instances with context bloat reduction features for efficient token usage.

Provides seamless access to the Fake Store API for AI assistants with 18 CRUD tools for managing e-commerce data including products, carts, and users. Perfect for e-commerce demos, testing, and learning MCP development with zero configuration required.

Provides code repository indexing and semantic search capabilities, allowing natural language queries to find relevant code snippets with automatic incremental indexing and multi-language support.

MCP server that launches Mesen/MesenCE headlessly and exposes the emulator's debugger-face Lua API over MCP JSON-RPC, enabling AI agents to load ROMs, step frames, inspect memory/registers, manage breakpoints/watches, trace execution, and export Code/Data Logger maps for SNES, NES, PC Engine, and Game Boy Advance.

A fake MCP server that emulates the Pennylane MCP experience for local development, testing, demos, and CI pipelines, providing deterministic fixtures and authentication modes without needing a real Pennylane account.

Centralizes multi-agent team workflows, providing Kanban, audit timeline, scorecards, and event hooks, integrated natively with Hermes Dashboard via the Model Context Protocol.

Enables building WebAR experiences using natural language through tools for Three.js scene creation, project management, and asset integration within 8th Wall Desktop. It supports advanced features like face tracking, image targets, and automated 3D model management.