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docs: add HF MCP Server section to agents page (#1770)
- Add new section documenting the official Hugging Face MCP Server - Explain seamless integration with MCP-compatible AI assistants (VSCode, Cursor, Claude Desktop) - Document built-in tools (Spaces/Papers search, Model/Dataset exploration) - Highlight MCP-compatible Gradio apps connectivity - Include getting started instructions and experimental status warning - Update page introduction to include HF MCP Server in the tools list
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docs/hub/agents.md

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# Agents on the Hub
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This page compiles all the libraries and tools Hugging Face offers for agentic workflows:
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- `HF MCP Server`: Connect your MCP-compatible AI assistant directly to the Hugging Face Hub.
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- `tiny-agents`: A lightweight toolkit for MCP-powered agents, available in both JS (`@huggingface/tiny-agents`) and Python (`huggingface_hub`).
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- `Gradio MCP Server`: Easily create MCP servers from Gradio apps and Spaces.
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- `smolagents`: a Python library that enables you to run powerful agents in a few lines of code.
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## HF MCP Server
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The official **Hugging Face MCP (Model Context Protocol) Server** enables seamless integration between the Hugging Face Hub and any MCP-compatible AI assistant—including VSCode, Cursor, and Claude Desktop.
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With the HF MCP Server, you can enhance your AI assistant's capabilities by connecting directly to the Hub's ecosystem. It comes with:
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- a curated set of **built-in tools** like Spaces and Papers Semantic Search, Model and Dataset exploration, etc
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- **MCP-compatible Gradio apps**: Connect to any [MCP-compatible Gradio app](https://huggingface.co/spaces?filter=mcp-server) built by the Hugging Face community
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#### Getting Started
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Visit [huggingface.co/settings/mcp](https://huggingface.co/settings/mcp) to configure your MCP client and get started.
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<Tip warning={true}>
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This feature is experimental ⚗️ and will continue to evolve.
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</Tip>
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## smolagents
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[smolagents](https://github.com/huggingface/smolagents) is a lightweight library to cover all agentic use cases, from code-writing agents to computer use, in few lines of code. It is model agnostic, supporting local models served with Hugging Face Transformers, as well as models offered with [Inference Providers](../inference-providers/index.md), and proprietary model providers.

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