Lilly Tech Systems
Learn MCP Server
Master the Model Context Protocol (MCP) — Anthropic's open standard that enables AI models to connect to external data sources and tools through standardized servers. Build, deploy, and integrate MCP servers that expose resources, tools, and prompts to AI assistants like Claude, Cline, and more.
Your Learning Path
Follow these lessons in order, or jump to any topic that interests you.
1. Introduction
What is MCP? Understand the Model Context Protocol, why it exists, and how it standardizes AI-tool integration.
2. Architecture
Deep dive into MCP architecture: transport layers, JSON-RPC messages, capabilities, connection lifecycle, and security.
3. Building Servers
Build an MCP server from scratch using TypeScript and Python SDKs. Complete working examples included.
4. Tools & Resources
Define MCP tools with input schemas, create URI-based resources, build prompt templates, and handle subscriptions.
5. Client Integration
Connect MCP servers to Claude Desktop, Claude Code CLI, Cline, Kilocode, and custom applications.
6. Popular MCP Servers
Explore filesystem, database, GitHub, Slack, Google Drive, Brave Search, Puppeteer, and community servers.
7. Deployment
Deploy MCP servers locally, remotely via HTTP/SSE, in Docker containers, and on cloud platforms.
8. Best Practices
Server design principles, security checklist, performance optimization, testing, and community guidelines.
What You'll Learn
By the end of this course, you'll be able to:
Connect AI to Anything
Build MCP servers that give AI models access to databases, APIs, file systems, and any external data source.
Build Custom Servers
Create MCP servers in TypeScript or Python with tools, resources, and prompts using official SDKs.
Deploy & Scale
Deploy MCP servers in production with Docker, cloud platforms, authentication, and monitoring.
Integrate Everywhere
Connect your servers to Claude Desktop, Claude Code, Cline, Kilocode, and custom AI applications.