mcp-server

The MCP (Model Context Protocol) server is a specialized server designed to handle and manage model context protocols efficiently. It serves as a bridge between various machine learning models and applications, ensuring seamless communication and data exchange. The server is built to support the integration of large language models (LLMs) and other advanced AI technologies, providing a robust platform for developers to deploy and manage their AI solutions. With its flexible architecture, the MCP server can be customized to meet specific requirements, making it an ideal choice for both personal and enterprise-level applications.

Features

• Seamless integration with LLMs and other AI models.
• Flexible architecture for customization and scalability.
• Efficient data exchange and communication management.
• Robust security features to protect data and models.
• User-friendly interface for easy deployment and management.

Usage with Different Platforms

python

python
import mcp

# Initialize the MCP server
server = mcp.Server()

# Configure server settings
server.configure(host='localhost', port=8080)

# Start the server
server.start()

docker

dockerfile
# Use an official Python runtime as a parent image
FROM python:3.8-slim

# Set the working directory in the container
WORKDIR /usr/src/app

# Copy the current directory contents into the container at /usr/src/app
COPY . .

# Install any needed packages specified in requirements.txt
RUN pip install --no-cache-dir -r requirements.txt

# Make port 8080 available to the world outside this container
EXPOSE 8080

# Run mcp-server when the container launches
CMD [ "python", "mcp_server.py" ]