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URL: https://glama.ai/mcp/servers/integrations/huggingface

⇱ Hugging Face | Glama

  • Why this server?

    Integrates with Hugging Face for model hosting and distribution, with links to MiniMax AI models on the platform.

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    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
    6
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    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

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    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
    4
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    25
    MIT

  • Why this server?

    Connects to MiniMax's Hugging Face organization to access related models and resources

  • Why this server?

    Enables interaction with various open-source AI models hosted on Hugging Face through the unified LiteLLM interface

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    Provides unified access to 100+ AI models from OpenAI, Anthropic, Google, AWS Bedrock and other providers through a single MCP interface. Enables seamless switching between different AI models using LiteLM's unified API without requiring separate integrations for each provider.
    Last updated
    3
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    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.

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    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
    GPL 3.0

  • Why this server?

    Enables ML model training, dataset management, and interaction with the Hugging Face Hub through specialized agent skills.

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    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
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  • Why this server?

    Allows for the safety inspection of machine learning models hosted on Hugging Face by scanning direct resolve URLs for malicious artifacts and deserialization risks.

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    ModelSafetyMCP is an MCP server for scanning machine learning model artifacts for unsafe serialization, malicious model patterns, risky packaging, URL-based artifact scanning, and directory-level triage.
    Last updated
    6
    MIT

  • Why this server?

    Allows interaction with the Hugging Face Dataset Viewer API, providing tools for browsing, searching, filtering, and analyzing datasets hosted on the Hugging Face Hub, along with support for authentication for private datasets.

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    Enables interaction with the Hugging Face Dataset Viewer API, allowing users to browse, search, filter, and analyze datasets hosted on the Hugging Face Hub.
    Last updated
    8
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    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.

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    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
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