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+# GPT-OSS Examples
+
+This directory contains practical examples demonstrating how to use gpt-oss models in different scenarios and with various frameworks.
+
+## Available Examples
+
+### [Streamlit Chat Interface](./streamlit/)
+A web-based chat application built with Streamlit that provides:
+- Interactive chat interface with conversation history
+- Model selection and configuration options
+- Function calling capabilities
+- Real-time streaming responses
+
+**Best for**: Quick prototyping, demos, and interactive testing of gpt-oss models.
+
+### [Agents SDK Python](./agents-sdk-python/)
+An advanced example using the OpenAI Agents SDK with:
+- Async agent interactions
+- Model Context Protocol (MCP) integration
+- Custom function tools
+- Filesystem operations
+- Streaming event processing
+
+**Best for**: Building sophisticated AI agents with tool capabilities and external integrations.
+
+## Getting Started
+
+Each example directory contains its own README with detailed setup and usage instructions. Generally, you'll need:
+
+1. **A local gpt-oss server running** (using Ollama, vLLM, or the gpt-oss responses API server)
+2. **Python dependencies** specific to each example
+3. **Additional tools** as specified in each example's requirements
+
+## Common Setup
+
+Most examples expect a local gpt-oss server compatible with OpenAI's API format. Here are quick setup options:
+
+### Using Ollama
+```bash
+ollama pull gpt-oss:20b
+ollama run gpt-oss:20b
+```
+
+### Using the gpt-oss Responses API Server
+```bash
+python -m gpt_oss.responses_api.serve --checkpoint /path/to/checkpoint --port 11434
+```
+
+### Using vLLM
+```bash
+python -m vllm.entrypoints.openai.api_server --model openai/gpt-oss-20b --port 11434
+```
+
+## Contributing Examples
+
+We welcome contributions of new examples! If you've built something interesting with gpt-oss, consider:
+
+1. Adding it to the [`awesome-gpt-oss.md`](../awesome-gpt-oss.md) file
+2. Creating a pull request with a new example directory
+3. Including a comprehensive README with setup instructions
+
+## Support
+
+For questions about these examples:
+- Check the individual example README files
+- Review the main [gpt-oss documentation](../README.md)
+- Visit the [OpenAI Cookbook](https://cookbook.openai.com/topic/gpt-oss) for more guides
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+# Agents SDK Python Example
+
+This example demonstrates how to use gpt-oss models with the OpenAI Agents SDK for Python, including integration with Model Context Protocol (MCP) servers.
+
+## Features
+
+- Async agent interaction with streaming responses
+- Integration with MCP servers for enhanced capabilities
+- Custom function tools
+- Filesystem operations through MCP
+- Real-time event processing
+
+## Prerequisites
+
+Before running this example, you need:
+
+1. **Node.js and npm** - Required for the MCP filesystem server
+2. **Local gpt-oss server** - Running on `http://localhost:11434`
+3. **Python 3.12+** - As specified in the project configuration
+
+## Installation
+
+1. Install Node.js and npm if not already installed
+2. Install the Python dependencies:
+
+```bash
+pip install openai-agents>=0.2.4
+```
+
+Or if you prefer using the project file:
+
+```bash
+pip install -e .
+```
+
+## Running the Example
+
+1. **Start your local gpt-oss server** (e.g., using Ollama):
+```bash
+ollama run gpt-oss:20b
+```
+
+2. **Run the example**:
+```bash
+python example.py
+```
+
+3. **Interact with the agent** by typing your message when prompted
+
+## How It Works
+
+The example sets up:
+
+1. **OpenAI Client**: Configured to connect to your local gpt-oss server
+2. **MCP Server**: Filesystem operations server via npx
+3. **Custom Tools**: A sample weather search function
+4. **Streaming Agent**: Processes responses in real-time
+
+## Example Interaction
+
+```
+> Can you tell me about the files in the current directory?
+Agent updated: My Agent
+-- Tool was called
+-- Tool output: [filesystem results]
+-- Message output: I can see several files in your current directory...
+=== Run complete ===
+```
+
+## Configuration
+
+You can customize the example by:
+
+- **Model**: Change the model name in the `Agent` configuration (line 70)
+- **Instructions**: Modify the agent's system instructions (line 68)
+- **Tools**: Add custom function tools using the `@function_tool` decorator
+- **Base URL**: Update the OpenAI client base URL for different servers
+
+## MCP Integration
+
+This example uses the Model Context Protocol (MCP) to provide the agent with filesystem capabilities. The MCP server is automatically started and connected, allowing the agent to:
+
+- Read and write files
+- List directory contents
+- Navigate the filesystem
+
+## Error Handling
+
+The example includes basic error handling:
+- Checks for `npx` availability before running
+- Graceful connection to MCP servers
+- Async/await pattern for proper resource management
+
+## Extending the Example
+
+To add more capabilities:
+
+1. **Add custom tools**:
+```python
+@function_tool
+async def my_custom_tool(param: str) -> str:
+    return f"Processed: {param}"
+```
+
+2. **Add more MCP servers**:
+```python
+additional_mcp = MCPServerStdio(name="Another Server", params={...})
+agent = Agent(..., mcp_servers=[mcp_server, additional_mcp])
+```
+
+3. **Process different event types**:
+```python
+async for event in result.stream_events():
+    if event.type == "your_custom_event_type":
+        # Handle custom events
+        pass
+```
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+# Streamlit Chat Example
+
+This example demonstrates how to create a web-based chat interface for gpt-oss models using Streamlit.
+
+## Features
+
+- Interactive chat interface with conversation history
+- Model selection (large/small)
+- Configurable reasoning effort (low/medium/high)
+- Function calling support with custom tools
+- Real-time streaming responses
+
+## Prerequisites
+
+Before running this example, you need:
+
+1. **Local gpt-oss server running** - This example expects a local API server compatible with OpenAI's chat completions format
+2. **Python packages** - Install the required dependencies
+
+## Installation
+
+1. Install Streamlit and requests:
+```bash
+pip install streamlit requests
+```
+
+2. Make sure you have a local gpt-oss server running (e.g., using Ollama, vLLM, or the gpt-oss responses API server)
+
+## Running the Example
+
+1. Start your local gpt-oss server on `http://localhost:11434` (or modify the base URL in the code)
+
+2. Run the Streamlit app:
+```bash
+streamlit run streamlit_chat.py
+```
+
+3. Open your browser to the URL displayed (typically `http://localhost:8501`)
+
+## Configuration
+
+The app provides several configuration options in the sidebar:
+
+- **Model**: Choose between "large" and "small" models
+- **Instructions**: Customize the system prompt for the assistant
+- **Reasoning effort**: Control the level of reasoning (low/medium/high)
+- **Functions**: Enable/disable function calling with a sample weather function
+
+## Customization
+
+You can customize this example by:
+
+- Modifying the base URL to point to your gpt-oss server
+- Adding custom functions in the function properties section
+- Changing the default system instructions
+- Styling the interface with Streamlit components
+
+## Notes
+
+- This example assumes you're running a local gpt-oss server compatible with OpenAI's API format
+- The function calling feature includes a sample weather function for demonstration
+- Conversation history is maintained during the session but not persisted between sessions
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