Hugging Face is an AI community building the future. They provide tools that enable users to build, train and deploy ML models based on open source code and technologies.
JavaScript implementation of MiniMax MCP that enables interaction with MiniMax AI services for image generation, video generation, text-to-speech, and voice cloning through MCP-compatible clients.
Last updated
10
682
122
MIT
Why this server?
Enables ML model training, dataset management, and interaction with the Hugging Face Hub through specialized agent skills.
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.
Last updated
4
18
22
MIT
Why this server?
Provides a similar user experience to Hugging Face for model access and deployment workflows
Provides tools for evaluating and benchmarking AI explanation methods through a standard interface that can be used with AI assistants and MCP-compatible applications.
Last updated
11
MIT
Why this server?
Integrates with Hugging Face's LocalPythonExecutor from the smolagents framework to provide secure Python code execution capabilities with basic isolation and security for running LLM-generated Python code.
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.
Last updated
1
44
MIT
Why this server?
Allows processing and analysis of datasets from Hugging Face, specifically the dair-ai/emotion dataset, with tools for sampling records, counting entries by emotion, searching text, and analyzing emotion distributions.
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.
Last updated
4
Why this server?
Connects to MiniMax's Hugging Face organization to access related models and resources
Enables MCP clients like Claude Desktop and Cursor to interact with MiniMax APIs for generating speech, cloning voices, creating videos, and generating images.
Last updated
6
1,418
MIT
Why this server?
Provides read-only access to Hugging Face Hub APIs, allowing interaction with models, datasets, spaces, papers, and collections. Includes tools for searching and retrieving detailed information across these resource types.
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.
Last updated
10
70
MIT
Why this server?
Supports automated ingestion of daily papers from Hugging Face via the pipeline function, which evaluates relevance, generates embeddings, deduplicates content, and integrates them into the knowledge base.
Personal knowledge graph with 16 MCP tools. Auto-links, deduplicates, tracks themes, synthesizes insights.
Last updated
17
4
MIT
Why this server?
Allows retrieval of daily featured papers, trending models, and popular datasets from Hugging Face Hub, providing insights into the latest developments in machine learning models.
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.
