python_mcp_agent

# Making an MCP Agent with Python This is an example of implementing a YouTube agent with YouTube search, summarization, and channel analysis features using MCP. ## Introduction to MCP (Model Context Protocol) - A standardized way for AI to effectively connect to tools of external data - Especially used a lot for standardized connection of various tools - **MCP Server**: Plays the role of defining and providing available tools - **MCP Client**: Imports and uses defined tools (Claude Desktop, Cursor, OpenAI Agents SDK) - In this example, we will create an MCP Server for YouTube content analysis and connect it with an MCP Client based on the OpenAI Agents SDK.  ## Initial Setup 1. Clone or download the repository ```bash git clone https://github.com/dabidstudio/python-mcp-agent.git cd python-mcp-agent ``` 2. [Issue an OpenAI key](https://github.com/dabidstudio/dabidstudio_guides/blob/main/get-openai-api-key.md) 3. [Issue a YouTube Data API Key](https://github.com/dabidstudio/dabidstudio_guides/blob/main/get-youtube-data-api.md) 4. Copy .env.example, enter the API key, and save as .env ```bash OPENAI_API_KEY=api_key_input YOUTUBE_API_KEY=api_key_input ``` 5. [Set up a Python virtual environment](https://github.com/dabidstudio/dabidstudio_guides/blob/main/python-set-venv.md) ```bash python -m venv venv venv\Scripts\activate # Mac is source venv/bin/activate ``` 6. Install packages ```bash pip install mcp openai-agents streamlit youtube-transcript-api python-dotenv requests ``` ## Preparation for MCP Client Integration To integrate a local MCP server with MCP client applications such as Claude and Cursor, you must enter the **Python executable path** and **MCP server script path** required to run the server in the JSON settings. - Modify mcp.json to match your path. ### Path Configuration Example #### ✅ Windows Example (e.g., if the project folder is `C:\projects\dabidstudio_videos\python_mcp_agent`) > **Note:** In Windows, you must use `\\` (double backslash) instead of `\` in JSON syntax. ```json { "mcpServers": { "mcp-test": { "command": "C:\\projects\\dabidstudio_videos\\python_mcp_agent\\venv\\Scripts\\python.exe", "args": [ "C:\\projects\\dabidstudio_videos\\python_mcp_agent\\2_mcp_server.py" ] } } } ``` --- #### ✅ macOS / Linux Example (e.g., if the project folder is `/Users/yourname/projects/python_mcp_agent`) ```json { "mcpServers": { "mcp-test": { "command": "/Users/yourname/projects/python_mcp_agent/venv/bin/python", "args": [ "/Users/yourname/projects/python_mcp_agent/2_mcp_server.py" ] } } } ``` --- ## Folder Structure ``` python-mcp-agent/ ├── 1_mcp_server_functions.ipynb # MCP server function example notebook ├── 2_mcp_server.py # MCP server implementation example ├── 3_openai_agents_basics.py # OpenAI Agent basic example ├── 4_mcp_client.py # Streamlit MCP Client example ├── .env.example # Environment variable example file └── mcp.json # MCP server configuration file ```