ksrk-mcp-server-client

## Requirements - Python 3.13 - Dependencies listed in `pyproject.toml` ## Installation 1. Clone the repository: ```sh git clone <repository-url> cd documentation ``` 2. Create a virtual environment and activate it: ```sh python -m venv .venv source .venv/bin/activate # On Windows use `.venv\Scripts\activate` ``` 3. Install the dependencies: ```sh pip install -r requirements.txt ``` 4. Set up environment variables: Create a `.env` file in the root directory with the following content: ```env SCRAPING_DOG_API_KEY=your_scraping_dog_api_key OPENAI_API_KEY=your_openai_api_key ``` ## Usage ### Running the Client 1. Navigate to the root directory: ```sh cd .. ``` 2. Run the client: ```sh python client.py ``` 3. Enter your prompts in the interactive prompt loop. Type `quit` or `exit` to stop the client. ## Project Files ### `client.py` This file contains the main client code that interacts with the MCP server and OpenAI's GPT-4 model. It includes the following key components: - `MCPClient`: A class that manages the connection to the MCP server and provides methods to retrieve available tools and call them. - `agent_loop`: An asynchronous function that processes user queries using the LLM and available tools. - `main`: The main function that sets up the MCP server, initializes tools, and runs the interactive loop. ### `ksrk-mcp/ksrk-mcp-server.py` This file contains the MCP server implementation. It includes the following key components: - `search_web`: An asynchronous function that searches the web using the ScrapingDog API. - `fetch_url`: An asynchronous function that fetches the content of a URL. - `about_ksrk`: An MCP tool that searches for details about "ksrk" on a given website. ### `ksrk-mcp/test-website.py` This file contains a script to test website scraping using `httpx` and `BeautifulSoup`. ## License This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details. ## Acknowledgements - [OpenAI](https://openai.com) for providing the GPT-4 model. - [ScrapingDog](https://scrapingdog.com) for the web scraping API. - [BeautifulSoup](https://www.crummy.com/software/BeautifulSoup/) for parsing HTML and XML documents. - [httpx](https://www.python-httpx.org) for the HTTP client.