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 9 months ago
10
657
114
MIT
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 3 months ago
6
1,396
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 9 months ago
1
45
MIT
Why this server?
Connects to Hugging Face Spaces, enabling access to various AI models and capabilities including image generation, vision tasks, text-to-speech, speech-to-text, and chat functionality with minimal setup.
Connects Claude Desktop to Hugging Face Spaces with minimal setup, enabling capabilities like image generation, vision tasks, text-to-speech, and chat with AI models.
Last updated a year ago
3
121
MIT
Why this server?
Enables deployment of the MCP server with a Gradio UI interface on Hugging Face's platform for web-based access to quantitative finance tools.
Provides AI agents with institutional-grade quantitative finance tools including real-time market data, paper trading via Alpaca, risk analysis with Monte Carlo simulations, backtesting, and multi-source news sentiment analysis for portfolio management and trading strategy development.
Last updated 3 months ago
31
5
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.
Last updated 5 months ago
8
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 9 months ago
11
MIT
Why this server?
Integrates with Hugging Face APIs to access the TSpec-LLM dataset containing 535M words of 3GPP specification data for direct specification search and analysis
Enables AI assistants to access and search 3GPP telecommunications specifications through direct integration with the TSpec-LLM dataset. Provides real-time specification content, implementation requirements, and multi-spec comparisons for 3GPP standards development.
Last updated 7 months ago
7
4
64
14
Why this server?
Integrates with Hugging Face models for document embeddings, supporting the semantic search functionality.
Enables LLM-based agents to interact with FHIR healthcare data through natural language prompts, providing full CRUD operations on FHIR resources, document processing, and semantic search capabilities.
