diff --git a/docs/hub/agents.md b/docs/hub/agents.md
index ed4ed827f..e49aaaffd 100644
--- a/docs/hub/agents.md
+++ b/docs/hub/agents.md
@@ -24,49 +24,10 @@ This feature is experimental ⚗️ and will continue to evolve.
 
 </Tip>
 
-## smolagents
-
-[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. 
-
-It offers a unique kind of agent :`CodeAgent`, an agent that writes its actions in Python code.
-It also supports the standard agent that writes actions in JSON blobs as most other agentic frameworks do, called `ToolCallingAgent`.
-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/).
-
-If you want to avoid defining agents yourself, the easiest way to start an agent is through the CLI, using the `smolagent` command.
-
-```bash
-smolagent "Plan a trip to Tokyo, Kyoto and Osaka between Mar 28 and Apr 7." \
---model-type "InferenceClientModel" \
---model-id "Qwen/Qwen2.5-Coder-32B-Instruct" \
---imports "pandas numpy" \
---tools "web_search"
-```
-
-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).
-
-smolagents also supports MCP servers as tools, as follows:
-
-```python
-# pip install --upgrade smolagents mcp
-from smolagents import MCPClient, CodeAgent
-from mcp import StdioServerParameters
-import os
-
-server_parameters = StdioServerParameters(
-    command="uvx",  # Using uvx ensures dependencies are available
-    args=["--quiet", "pubmedmcp@0.1.3"],
-    env={"UV_PYTHON": "3.12", **os.environ},
-)
-
-with MCPClient(server_parameters) as tools:
-    agent = CodeAgent(tools=tools, model=model, add_base_tools=True)
-    agent.run("Please find the latest research on COVID-19 treatment.")
-```
-
-Learn more [in the documentation](https://huggingface.co/docs/smolagents/tutorials/tools#use-mcp-tools-with-mcpclient-directly).
-
 ## tiny-agents (JS and Python)
 
+NEW: tiny-agents now supports [AGENTS.md](https://agents.md/) standard. 🥳
+
 `tiny-agents` is a lightweight toolkit for running and building MCP-powered agents on top of the Hugging Face Inference Client + Model Context Protocol (MCP). It is available as a JS package `@huggingface/tiny-agents` and in the `huggingface_hub` Python package.
 
 
@@ -234,3 +195,43 @@ Lastly, add this to the settings of the MCP Client of your choice (e.g. Cursor).
 
 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).
 
+## smolagents
+
+[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. 
+
+It offers a unique kind of agent :`CodeAgent`, an agent that writes its actions in Python code.
+It also supports the standard agent that writes actions in JSON blobs as most other agentic frameworks do, called `ToolCallingAgent`.
+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/).
+
+If you want to avoid defining agents yourself, the easiest way to start an agent is through the CLI, using the `smolagent` command.
+
+```bash
+smolagent "Plan a trip to Tokyo, Kyoto and Osaka between Mar 28 and Apr 7." \
+--model-type "InferenceClientModel" \
+--model-id "Qwen/Qwen2.5-Coder-32B-Instruct" \
+--imports "pandas numpy" \
+--tools "web_search"
+```
+
+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).
+
+smolagents also supports MCP servers as tools, as follows:
+
+```python
+# pip install --upgrade smolagents mcp
+from smolagents import MCPClient, CodeAgent
+from mcp import StdioServerParameters
+import os
+
+server_parameters = StdioServerParameters(
+    command="uvx",  # Using uvx ensures dependencies are available
+    args=["--quiet", "pubmedmcp@0.1.3"],
+    env={"UV_PYTHON": "3.12", **os.environ},
+)
+
+with MCPClient(server_parameters) as tools:
+    agent = CodeAgent(tools=tools, model=model, add_base_tools=True)
+    agent.run("Please find the latest research on COVID-19 treatment.")
+```
+
+Learn more [in the documentation](https://huggingface.co/docs/smolagents/tutorials/tools#use-mcp-tools-with-mcpclient-directly).
\ No newline at end of file