AI TRAINING
Model Context Protocol (MCP) for Developers
Build production-ready MCP servers and clients with secure authentication and robust integration patterns.
What it covers
This hands-on technical programme equips platform engineers and integrators with deep working knowledge of the Model Context Protocol — from architecture fundamentals to production deployment. Participants will write MCP servers and clients from scratch, implement authentication and authorisation patterns, handle transport layers, and integrate with AI coding tools such as Claude Code. The course covers security hardening, error handling, schema design, and common implementation pitfalls through live coding exercises and peer code review.
What you'll be able to do
- Implement a fully functional MCP server exposing tools, resources, and prompt templates over stdio and HTTP/SSE transports
- Write an MCP client that discovers, connects to, and safely invokes server-exposed tools
- Apply OAuth 2.0 and API-key authentication patterns to secure MCP endpoints in production
- Identify and mitigate the top security risks in MCP deployments, including prompt injection and over-permissioned tools
- Integrate a custom MCP server with Claude Code and validate end-to-end tool calling behaviour
Topics covered
- MCP architecture: protocol spec, JSON-RPC transport, stdio vs HTTP/SSE
- Writing MCP servers in Python and TypeScript
- Writing MCP clients and managing server discovery
- Authentication patterns: OAuth 2.0, API keys, and token scoping
- Security hardening: prompt injection risks, tool permission scoping, sandboxing
- Schema design for tools, resources, and prompts
- Integration with Claude Code and other MCP-compatible hosts
- Debugging, error handling, and common implementation mistakes
Delivery
Delivered as a 2-3 day intensive bootcamp, either in-person or live-virtual (Zoom/Teams). Each day combines a 30% concept session with 70% hands-on coding labs. Participants require a laptop with Node.js 18+ and Python 3.10+ pre-installed. A shared GitHub repository with starter templates and test harnesses is provided. Optional asynchronous follow-up office hours (2 × 1 h) are included in the standard package.
What makes it work
- Start with a real internal use case (e.g., exposing a database or internal API) so labs are immediately relevant
- Establish a security review checklist for MCP server PRs before the bootcamp ends
- Pair each developer with a code-review partner to surface hidden assumptions in schema design
- Run integration tests against a local Claude Code or MCP-compatible host as part of the CI pipeline from day one
Common mistakes
- Exposing overly broad tool permissions without scoping, allowing AI hosts to invoke destructive operations unintentionally
- Implementing authentication as an afterthought rather than at the transport layer from the start
- Conflating MCP resources (read-only context) with tools (side-effectful actions), leading to misused schema design
- Skipping input validation on tool arguments, creating injection vectors when LLM-generated payloads are passed directly
When NOT to take this
This training is not the right fit for teams that have not yet committed to using an MCP-compatible AI host in production — the protocol is meaningless without a concrete integration target, and participants will not be able to ground the labs in real work.
Providers to consider
Sources
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