Simple Model Context Protocol MCP
This project is a simple demonstration of the Model Context Protocol (MCP), designed to facilitate seamless integration between clients and servers. It provides a standardized way for large language models (LLMs) to interact with external tools and data sources. This project showcases the use of MCP for client-server communication, CRUD operations, and integrating model context in applications.
What is the Model Context Protocol (MCP)?
The Model Context Protocol (MCP) is an open protocol that enables easy integration of external tools and data sources with large language models (LLMs). It provides a common standard for exchanging model context, making it easier to build context-aware AI applications, such as:
- AI-powered IDEs
- Custom AI workflows
- Chat interfaces with real-time context updating
MCP ensures that LLMs have access to the context they need by connecting them with external data and tools.
Features
This project demonstrates the following capabilities:
- Client-Server Communication: Uses MCP to facilitate communication between the client and server.
- CRUD Operations: Allows creating, reading, updating, and deleting notes stored in an SQLite database.
- Random Seed Generation and Echo: Includes a tool for generating a random seed and echoing it back along with the input message.
- SQLite Database Integration: Demonstrates how to interact with an SQLite database using Entity Framework Core (EF Core) for storing and retrieving notes.
Project Structure
- MCPServer: Contains the server-side implementation, including CRUD operations on notes and the echo tool.
- MCPClient: Simulates a client that communicates with the server using the MCP protocol.
- ModelContextProtocol: The core protocol library that defines the standards for model context exchange.
Technologies Used
- C# (.NET Core 9.0)
- SQLite: A lightweight database used for storing notes.
- Entity Framework Core: ORM used for data access and manipulation.
- MCP Protocol: Standard protocol for client-server communication in AI-powered applications.
