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docs/hub/agents.md

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This page compiles all the libraries and tools Hugging Face offers for agentic workflows: huggingface.js mcp-client, Gradio MCP Server and smolagents.
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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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It offers a unique kind of agent :`CodeAgent`, an agent that writes its actions in Python code.
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It also supports the standard agent that writes actions in JSON blobs as most other agentic frameworks do, called `ToolCallingAgent`.
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To learn more about write actions in code vs JSON, check out our [new short course on DeepLearning.AI](https://www.deeplearning.ai/short-courses/building-code-agents-with-hugging-face-smolagents/).
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If you want to avoid defining agents yourself, the easiest way to start an agent is through the CLI, using the `smolagent` command.
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```bash
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smolagent "Plan a trip to Tokyo, Kyoto and Osaka between Mar 28 and Apr 7." \
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--model-type "InferenceClientModel" \
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--model-id "Qwen/Qwen2.5-Coder-32B-Instruct" \
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--imports "pandas numpy" \
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--tools "web_search"
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```
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Agents can be pushed to Hugging Face Hub as Spaces. Check out all the cool agents people have built [here](https://huggingface.co/spaces?filter=smolagents&sort=likes).
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smolagents also supports MCP servers as tools, as follows:
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```python
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# pip install --upgrade smolagents mcp
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from smolagents import MCPClient, CodeAgent
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from mcp import StdioServerParameters
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import os
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server_parameters = StdioServerParameters(
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command="uvx", # Using uvx ensures dependencies are available
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args=["--quiet", "[email protected]"],
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env={"UV_PYTHON": "3.12", **os.environ},
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)
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with MCPClient(server_parameters) as tools:
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agent = CodeAgent(tools=tools, model=model, add_base_tools=True)
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agent.run("Please find the latest research on COVID-19 treatment.")
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```
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Learn more [in the documentation](https://huggingface.co/docs/smolagents/tutorials/tools#use-mcp-tools-with-mcpclient-directly).
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## huggingface.js mcp-client
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Huggingface.js offers an MCP client served with [Inference Providers](https://huggingface.co/docs/inference-providers/en/index) or local LLMs. Getting started with them is as simple as running `pnpm agent`. You can plug and play different models and providers by setting `PROVIDER` and `MODEL_ID` environment variables.
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This is very powerful because it lets the LLM use any Gradio application as a tool. You can find thousands of them on [Spaces](https://huggingface.co/spaces). Learn more [here](https://www.gradio.app/guides/building-mcp-server-with-gradio).
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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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It offers a unique kind of agent :`CodeAgent`, an agent that writes its actions in Python code.
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It also supports the standard agent that writes actions in JSON blobs as most other agentic frameworks do, called `ToolCallingAgent`.
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To learn more about write actions in code vs JSON, check out our [new short course on DeepLearning.AI](https://www.deeplearning.ai/short-courses/building-code-agents-with-hugging-face-smolagents/).
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If you want to avoid defining agents yourself, the easiest way to start an agent is through the CLI, using the `smolagent` command.
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```bash
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smolagent "Plan a trip to Tokyo, Kyoto and Osaka between Mar 28 and Apr 7." \
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--model-type "InferenceClientModel" \
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--model-id "Qwen/Qwen2.5-Coder-32B-Instruct" \
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--imports "pandas numpy" \
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--tools "web_search"
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```
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Agents can be pushed to Hugging Face Hub as Spaces. Check out all the cool agents people have built [here](https://huggingface.co/spaces?filter=smolagents&sort=likes).
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smolagents also supports MCP servers as tools, as follows:
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```python
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# pip install --upgrade smolagents mcp
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from smolagents import MCPClient, CodeAgent
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from mcp import StdioServerParameters
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import os
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server_parameters = StdioServerParameters(
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command="uvx", # Using uvx ensures dependencies are available
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args=["--quiet", "[email protected]"],
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env={"UV_PYTHON": "3.12", **os.environ},
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)
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with MCPClient(server_parameters) as tools:
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agent = CodeAgent(tools=tools, model=model, add_base_tools=True)
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agent.run("Please find the latest research on COVID-19 treatment.")
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```
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Learn more [in the documentation](https://huggingface.co/docs/smolagents/tutorials/tools#use-mcp-tools-with-mcpclient-directly).

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