This guide helps you build MCP servers. MCP stands for Model Context Protocol. It lets AI assistants connect to outside tools and data. You will learn to design, build, test, and deploy these servers. The purpose is to give AI agents real abilities like searching, creating, or reading information.
Anyone building AI tools can benefit. You will create tools that AI calls, resources that AI reads, and prompts that guide workflows. The process is clear and step by step. You will use either TypeScript or Python with safe libraries.
Important ideas include naming tools well, validating inputs, handling errors, and testing both logic and full connections. Safety rules protect data and prevent attacks. At the end you will have a production-ready server that makes your AI assistant much more capable.
Global
mkdir -p ~/.claude/skills/mcp-builderProject
mkdir -p .claude/skills/mcp-builderSource Repository
Find Skillsvercel-labs/skills
Find and install the perfect skill to extend your AI agent
Microsoft Foundrymicrosoft/azure-skills
Build, deploy, and improve AI agents on Microsoft Foundry from start to finish
Azure Aimicrosoft/azure-skills
Search, transcribe, and analyze with Azure AI tools for smarter apps
Azure Hosted Copilot Sdkmicrosoft/azure-skills
Build, deploy, and manage your Copilot SDK apps on Azure with ease
Triagemattpocock/skills
Triage issues with a state machine driven by clear roles and agent briefs
Handoffmattpocock/skills
Hand off your work to another AI agent with a clear summary
Image Editagentspace-so/runcomfy-agent-skills
Smart router picks the best AI model for your image editing needs
Agentspaceagentspace-so/skills
See your AI agent's live folder from any browser instantly