MCP Mastery: 100 Labs for Secure Enterprise AI Servers

About this course

This course contains the use of artificial intelligence.

We only charge a fee solely for the time invested in building this comprehensive curriculum.

MCP Mastery is a hands-on course for backend and AI engineers who want to build Model Context Protocol servers that connect enterprise data to AI systems securely. Across 100 labs you go from your first local MCP server to a hardened, authenticated, policy-enforced deployment that serves real enterprise data sources behind Kubernetes.

Anyone can wire an LLM to a tool over stdio on their laptop. Connecting that same model to a production SQL database, a document store, or live financial data, without leaking rows the caller isn’t authorized to see, without an unauthenticated endpoint sitting on the network, and with an audit trail someone can actually review, is a different problem. This course is built around that exact gap: not “what is MCP,” but “how do you run an MCP server that a security team signs off on.”

How the course works

Each of the 100 labs is a focused build with a title that states what you make, such as a resource template, an mTLS handshake, an OPA policy check, or a Kubernetes deployment. You build it, run it, and verify it works before moving on. What you’ll work withMCP servers and clients: resources, tools, prompts, and resource templates

Pydantic validation, async tool execution, and server-sent eventsmTLS, internal CA certificates, JWT, and OAuth2 for authenticationSQL with row-level security, Pinecone/Milvus, Neo4j, Kafka, S3, and RedisRBAC, ABAC, and Open Policy Agent for authorization

Docker, Kubernetes, Istio, Terraform, and HashiCorp VaultGitHub Actions CI/CD, Prometheus, and GrafanaMulti-server orchestration, tool chaining, and human-in-the-loop controls

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