Ksrk Mcp Server Client
MCP server to get latest information about me (for now), you can add that mcp server to claude desktop or create custom client which you can see in the file
karan-ksrk
README
Requirements
- Python 3.13
- Dependencies listed in
pyproject.toml
Installation
-
Clone the repository:
git clone <repository-url> cd documentation
-
Create a virtual environment and activate it:
python -m venv .venv source .venv/bin/activate # On Windows use `.venv\Scripts\activate`
-
Install the dependencies:
pip install -r requirements.txt
-
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
-
Navigate to the root directory:
cd ..
-
Run the client:
python client.py
-
Enter your prompts in the interactive prompt loop. Type
quit
orexit
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.
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