This project implements an MCP-compliant server that allows AI models to discover and invoke tools through a standardized protocol. The server is designed to be modular, with each tool implemented as a separate Python module.
Overview
what is MCP Server?
MCP Server is a scalable and modular implementation of the Model Context Protocol (MCP) that enables AI models to discover and invoke tools through a standardized protocol.
how to use MCP Server?
To use MCP Server, install the required dependencies using pip install -r requirements.txt, and then run the server with the command python -m src.server.
key features of MCP Server?
- Modular architecture allowing easy addition of new tools.
- Compliance with the Model Context Protocol for standardized tool invocation.
- Built using Python, making it accessible for developers familiar with the language.
use cases of MCP Server?
- Integrating various AI tools into a single server environment.
- Facilitating communication between AI models and external tools.
- Enabling developers to create and manage custom tools easily.
FAQ from MCP Server?
- What is the purpose of MCP Server?
MCP Server allows AI models to interact with tools in a standardized way, enhancing their capabilities.
- How can I add new tools to the server?
You can add new tools by creating a new Python file in the
src/toolsdirectory and using the@tooldecorator.
- Is MCP Server open-source?
Yes, MCP Server is available on GitHub and can be modified as per your needs.