MCP Template Node
A template repository for creating Model Context Protocol (MCP) servers in Node.js/TypeScript. This template demonstrates how to build a simple notes management system using the MCP protocol, which can be used with LLM-powered applications.
What is MCP Template Node?
What is MCP Template Node? MCP Template Node is a template repository designed for creating Model Context Protocol (MCP) servers using Node.js and TypeScript. It serves as a foundational framework for building a simple notes management system that can be integrated with LLM-powered applications. How to use MCP Template Node? To use MCP Template Node, clone the repository, install the dependencies, build the project, and run the server. You can also start the TypeScript compiler in watch mode for development. Key features of MCP Template Node? TypeScript implementation with strict type checking Simple notes management system with create, list, and get operations In-memory storage that can be easily replaced with a database Comprehensive error handling and validation GitHub Actions CI workflow for testing and building Use cases of MCP Template Node? Building LLM-powered applications that require context management. Creating custom note-taking applications using the MCP protocol. Developing modular and maintainable AI-powered applications. FAQ from MCP Template Node? What is the Model Context Protocol (MCP)? MCP is a standardized way for applications to provide context to Large Language Models (LLMs), allowing for more modular and maintainable AI applications. What are the prerequisites for using this template? You need Node.js 18 or later and npm or yarn to manage dependencies. How can I extend the template? You can add new tools by creating type definitions, error types, and tool implementations, then registering them in the server.
As an MCP (Model Context Protocol) server, MCP Template Node enables AI agents to communicate effectively through standardized interfaces. The Model Context Protocol simplifies integration between different AI models and agent systems.
How to use MCP Template Node
To use MCP Template Node, clone the repository, install the dependencies, build the project, and run the server. You can also start the TypeScript compiler in watch mode for development. Key features of MCP Template Node? TypeScript implementation with strict type checking Simple notes management system with create, list, and get operations In-memory storage that can be easily replaced with a database Comprehensive error handling and validation GitHub Actions CI workflow for testing and building Use cases of MCP Template Node? Building LLM-powered applications that require context management. Creating custom note-taking applications using the MCP protocol. Developing modular and maintainable AI-powered applications. FAQ from MCP Template Node? What is the Model Context Protocol (MCP)? MCP is a standardized way for applications to provide context to Large Language Models (LLMs), allowing for more modular and maintainable AI applications. What are the prerequisites for using this template? You need Node.js 18 or later and npm or yarn to manage dependencies. How can I extend the template? You can add new tools by creating type definitions, error types, and tool implementations, then registering them in the server.
Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.
Use Cases for this MCP Server
- No use cases specified.
MCP servers like MCP Template Node can be used with various AI models including Claude and other language models to extend their capabilities through the Model Context Protocol.
About Model Context Protocol (MCP)
The Model Context Protocol (MCP) is a standardized way for AI agents to communicate with various services and tools. MCP servers like MCP Template Node provide specific capabilities that can be accessed through a consistent interface, making it easier to build powerful AI applications with complex workflows.
Browse the MCP Directory to discover more servers and clients that can enhance your AI agents' capabilities.