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ksrk-mcp-server

by karan-ksrk

The ksrk-mcp-server-client project implements a client-server architecture for interacting with OpenAI's GPT-4 model, utilizing web scraping tools. The server provides tools like web search and URL fetching, while the client allows users to interact with these tools through an interactive prompt loop.

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What is ksrk-mcp-server?

The ksrk-mcp-server is a server-client application that leverages OpenAI's GPT-4 model and web scraping tools. It provides an MCP (Meta-Control Protocol) server that exposes functionalities like web searching and URL fetching, enabling the client to interact with these tools via an interactive prompt loop.

How to use ksrk-mcp-server?

To use the server, first clone the repository, set up a virtual environment, and install the necessary dependencies. Configure the .env file with your ScrapingDog and OpenAI API keys. Then, run the ksrk-mcp-server.py file to start the server. To use the client, navigate to the root directory and run python client.py. Enter your prompts in the interactive prompt loop. Type quit or exit to stop the client.

Key features of ksrk-mcp-server

  • Web searching using ScrapingDog API

  • URL content fetching

  • Interactive client prompt loop

  • MCP server implementation

  • Integration with OpenAI's GPT-4 model

Use cases of ksrk-mcp-server

  • Automated information retrieval

  • AI-powered web research

  • Building custom tools for interacting with web data

  • Integrating web scraping capabilities into AI applications

FAQ from ksrk-mcp-server

What is the purpose of the ScrapingDog API key?

The ScrapingDog API key is required to use the web searching functionality provided by the server.

What is the purpose of the OpenAI API key?

The OpenAI API key is required to interact with the GPT-4 model, which is used to process user queries and generate responses.

How do I install the dependencies?

Create a virtual environment, activate it, and then run pip install -r requirements.txt.

What is the MCP server?

The MCP server is a component that exposes the web scraping functionalities and allows the client to interact with them.

What does the client do?

The client provides an interactive prompt loop where users can enter queries, which are then processed by the GPT-4 model and the available web scraping tools.