MCP (Model Context Protocol) 서버

What is MCP Server? MCP Server is a service that integrates and manages various Large Language Models (LLMs) while providing a standardized interface. This project combines the DeepSeek and Llama models, allowing for easy switching between models and context management through an API. How to use MCP Server? To use MCP Server, clone the repository from GitHub, run the setup script to install dependencies and download models, and then start the server using either a virtual environment or Docker. Key features of MCP Server? Integration and management of various LLM models (DeepSeek, Llama) Easy switching and routing between models Conversation context management Standardized API interface Support for various storage backends (memory, Redis, SQLite) Use cases of MCP Server? Managing multiple LLMs for different applications. Providing a unified API for accessing various language models. Facilitating context-aware conversations in applications. FAQ from MCP Server? What models are supported by MCP Server? MCP Server currently supports DeepSeek and Llama models. Is MCP Server easy to set up? Yes! The setup process is straightforward, with detailed instructions provided in the documentation. Can I add new models to MCP Server? Yes! You can add new models by creating a new model class and updating the routing configuration.

As an MCP (Model Context Protocol) server, MCP (Model Context Protocol) 서버 enables AI agents to communicate effectively through standardized interfaces. The Model Context Protocol simplifies integration between different AI models and agent systems.

To use MCP Server, clone the repository from GitHub, run the setup script to install dependencies and download models, and then start the server using either a virtual environment or Docker. Key features of MCP Server? Integration and management of various LLM models (DeepSeek, Llama) Easy switching and routing between models Conversation context management Standardized API interface Support for various storage backends (memory, Redis, SQLite) Use cases of MCP Server? Managing multiple LLMs for different applications. Providing a unified API for accessing various language models. Facilitating context-aware conversations in applications. FAQ from MCP Server? What models are supported by MCP Server? MCP Server currently supports DeepSeek and Llama models. Is MCP Server easy to set up? Yes! The setup process is straightforward, with detailed instructions provided in the documentation. Can I add new models to MCP Server? Yes! You can add new models by creating a new model class and updating the routing configuration.

Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.