Introduction to MCP Framework

This framework makes it easy to create and manage MCP (modelcontextprotocol) servers that can be used with MCP Clients like the Claude Desktop app.

It is simple and intuitive to use.

MCP-Framework gives you architecture out of the box, with automatic directory-based discovery for tools, resources, and prompts. Use our powerful MCP abstractions to define tools, resources, or prompts in an elegant way. Our cli makes getting started with your own MCP server a breeze

Quickstart Guide

Key Features

• Tool Support: Create custom tools that extend AI model capabilities
• Resource Management: Handle external data sources and APIs
• Prompt Templates: Define reusable prompt templates
• Multiple Transports: Support for STDIO, HTTP Stream (recommended), and SSE communication
• Authentication: Built-in OAuth 2.1 (recommended), JWT, and API Key authentication
• Use the power of Typescript: Full TypeScript support with type safety
• CLI Tool: Easy project scaffolding and component creation
• Fast Development: Elegant and fast development cycles

How It Works

MCP Framework provides four main components:

1. Tools

Functions that AI models can invoke to:

• Fetch data from APIs
• Transform data
• Perform computations
• Interact with external services

2. Resources

Data sources that can be:

• Read by the AI model
• Subscribed to for updates
• Used to provide context

3. Prompts

Template systems that:

• Define reusable conversation flows
• Provide structured context
• Guide model interactions

4. Transports

Communication layers that:

• Handle client-server communication
• Support different use cases:
  • STDIO: Perfect for CLI tools and local integrations
  • HTTP Stream (Recommended): Modern transport for web applications with authentication, session management, and stream resumability
  • SSE (Deprecated): Legacy transport, replaced by HTTP Stream

The framework handles all communication between your server and AI models, following the Model Context Protocol specification.

When to Use MCP Framework

• Building custom tools for AI models
• Creating data integration services
• Developing specialized AI assistants
• Extending AI capabilities with external services
• Building enterprise AI solutions
• Creating web-based AI tools (using HTTP Stream transport)
• Developing secure AI services with OAuth 2.1 authentication

Ready to get started? Head to the Installation guide to begin building your first MCP server, or learn more about our transport options.