MCP Framework

MCP Framework – A TypeScript‑First Tool for Building Model Context Protocol Servers

MCP Framework addresses the recurring pain point of wiring up a fully‑featured MCP server from scratch. Developers who want to expose custom tools, prompts, or data sources to AI assistants such as Claude often find themselves reinventing directory structures, transport adapters, and validation logic. MCP Framework delivers a ready‑made architecture that automatically discovers and loads tools, resources, and prompts from the file system, freeing teams to focus on business logic rather than plumbing.

At its core, the framework is a thin wrapper around the official MCP SDK. It provides a set of base classes and decorators that let you declare tools, prompts, or resources in plain TypeScript. Because the entire stack is typed, compile‑time errors surface early, and IDEs can offer rich autocompletion. The CLI scaffolds new projects, generates boilerplate for each component type, and bundles a lightweight build pipeline that includes schema validation. This validation ensures that every Zod‑based input schema carries descriptive field metadata, a requirement for clear tool documentation in MCP clients.

Key capabilities include:

• Automatic discovery: Tools, prompts, and resources placed in designated folders are loaded without manual registration.
• Transport versatility: The server can communicate over stdio, Server‑Sent Events (SSE), or HTTP streaming, allowing seamless integration with diverse client architectures.
• Built‑in authentication: SSE endpoints come preconfigured with an authentication layer, simplifying secure deployments.
• CLI tooling: Commands for creating projects, adding components, building, and validating make iterative development fast and error‑free.

Real‑world scenarios that benefit from MCP Framework are plentiful. A crypto tipping service can expose wallet validation and tip‑preparation tools, letting an AI assistant guide users through sending payments. A data analytics platform can offer market‑data prompts and calculation tools that the assistant can invoke on demand. Because the framework is agnostic to transport, teams can expose services to local agents via stdio during development and later switch to HTTP for cloud‑based deployments without code changes.

In short, MCP Framework removes the operational overhead of building an MCP server, giving developers a type‑safe, modular foundation that scales from prototype to production. It enables AI assistants to tap into custom logic and data with minimal friction, accelerating the delivery of intelligent, context‑aware experiences.