MCP Starter provides a foundational template for building Model Context Protocol (MCP) servers. These servers act as crucial middleware, connecting AI clients to external tools, data, and services. It empowers AI models to interact with real-world applications. The template primarily uses TypeScript, offering a structure for developers to define and expose callable functions and resources. This program helps integrate AI with diverse external systems and data sources.

What does MCP Starter connect to?

MCP Starter creates servers that link AI clients, also known as hosts, with external tools and resources. It enables AI models to access data, applications, and services beyond their native capabilities. Compatible AI clients include Claude (Desktop/Code), Cursor, and VS Code with the MCP extension. Communication between client and server uses standard transport protocols like stdio and Streamable HTTP, with Streamable HTTP supporting Server-Sent Events for real-time responses.

Core features and tools

MCP Starter templates establish the basic structure for developers to define and expose specific callable tools. While the templates do not include a fixed set of tools, examples that can be implemented are get_forecast, get_alerts, database_query, and email_sender. MCP servers generally offer three main capabilities: Resources for file-like data, Tools as functions callable by an LLM, and Prompts as pre-written templates for tasks.

Who is it for?

MCP Starter is designed for developers building AI assistant tools and those integrating AI with external systems. It suits those who need to extend AI model capabilities by connecting them to real-world applications and data. This program is ideal for creating custom AI agents that interact with enterprise platforms or specialized services. Skip this if you are not a developer aiming to build AI middleware or integrate AI with external systems.

How to get started

Access is granted through a standard OAuth authorization flow, with Key-based authentication also supported. The server often uses stdio for local integration and prototyping.

Use cases

• Automating repetitive tasks, such as meal planning, generating shopping lists, and printing recipes.
• Connecting AI models to real-world tools and services, for instance, enabling an AI agent to fetch weather forecasts and alerts.
• Integrating with enterprise systems like Google Drive, Slack, GitHub, Postgres, and Puppeteer for tasks like documentation generation and report creation.

MCP Starter offers a strong framework for developers to create AI middleware servers, bridging AI models with external applications and data. It supports various transport protocols and a formalized OAuth 2.1 authentication model, making it suitable for secure enterprise integrations. The program empowers AI agents to perform real-world actions and automate complex workflows.