Module 06 — MCP (Model Context Protocol)

Name: Harness Engineering — Claude Code Mastery
Price: 89 EUR
Availability: InStock

In this module

You'll learn how to connect Claude Code to external tools (databases, Jira, Linear, GitHub) via the MCP protocol, install and configure MCP servers, handle authentication, and set up governance for your team.

Contents

6.1 — What is MCP? The universal AI-to-tools protocol Key takeaways 6.2 — MCP transports: HTTP, SSE, and Stdio Key takeaways

6.3 — Your first MCP server: step-by-step install Key takeaways 6.4 — MCP scopes: local, project, user Key takeaways 6.5 — MCP authentication: OAuth, headers, headersHelper Key takeaways 6.6 — MCP for databases Key takeaways 6.7 — MCP for project management: Jira, Linear, GitHub Key takeaways 6.8 — MCP Resources and Prompts Key takeaways 6.9 — Security and governance: managed-mcp.json Key takeaways 6.10 — claude mcp serve: Claude Code as an MCP server Key takeaways

6.1 — What is MCP? The universal AI-to-tools protocol Key takeaways 6.2 — MCP transports: HTTP, SSE, and Stdio Key takeaways

6.1 — What is MCP? The universal AI-to-tools protocol

Until now, every AI tool had to build its own integrations with every external service. One AI client, ten tools: ten specific integrations, each with its own format, authentication, and limitations. Three AI clients, ten tools: thirty integrations. MCP -- Model Context Protocol -- eliminates this complexity.

MCP is an open, standardized protocol that defines how an AI assistant communicates with external tools. Think USB-C: a single universal connector. Each tool is implemented once as an MCP server, and every compatible AI client understands it natively. You go from N x M integrations to N + M.

The architecture is built on a client-server model. Claude Code acts as the **MCP clien

Locked content

Unlock the full course to access this module.

Unlock

Already purchased? Recover access