Ksrk Mcp Server Client

What is Ksrk Mcp Server Client

ksrk-mcp-server-client is a client application designed to interact with the MCP server to retrieve the latest information about the user. It can be integrated into applications like Claude Desktop or used to create custom clients.

Use cases

Use cases include building custom chatbots, creating applications that require real-time data scraping, and enhancing user interaction through AI-driven responses.

How to use

To use ksrk-mcp-server-client, clone the repository, set up a virtual environment, install dependencies, configure environment variables, and run the client using Python. Users can enter prompts in an interactive loop.

Key features

Key features include an asynchronous client-server architecture, integration with OpenAI’s GPT-4 model, web scraping capabilities using the ScrapingDog API, and an interactive command-line interface for user queries.

Where to use

ksrk-mcp-server-client can be used in various fields such as software development, data retrieval, and AI applications where real-time information access is required.

Requirements

• Python 3.13
• Dependencies listed in pyproject.toml

Installation

1. Clone the repository:

   git clone <repository-url>
   cd documentation
   

2. Create a virtual environment and activate it:

   python -m venv .venv
   source .venv/bin/activate  # On Windows use `.venv\Scripts\activate`
   

3. Install the dependencies:

   pip install -r requirements.txt
   

4. Set up environment variables:

   Create a .env file in the root directory with the following content:

   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:

   cd ..
   

2. Run the client:

   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 file for details.

Acknowledgements

• OpenAI for providing the GPT-4 model.
• ScrapingDog for the web scraping API.
• BeautifulSoup for parsing HTML and XML documents.
• httpx for the HTTP client.