Training course · Model Context Protocol (MCP) · JavaScript & TypeScript

Model Context Protocol (MCP) for JavaScript and TypeScript Developers

Build and connect MCP servers securely: tools, resources and prompts for Claude Code, Cursor, Copilot and your own AI agents.

Duration
2 days (14 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

“Model Context Protocol (MCP) for JavaScript and TypeScript Developers” is a hands-on course for roles such as Front-end and full-stack developers working in JavaScript or TypeScript, Teams migrating an existing JavaScript codebase to TypeScript and Library and SDK maintainers in the npm ecosystem. Rather than learning Model Context Protocol (MCP) in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from JavaScript & TypeScript.

The Model Context Protocol is an open standard that gives AI applications a uniform way to access external tools, data sources and workflows. Instead of building separate integrations for every assistant, you implement an MCP server once and use it in Claude Code, Claude Desktop, Cursor, GitHub Copilot, VS Code and your own agents. In this two-day course you learn the host, client and server architecture, the three core primitives of tools, resources and prompts, and the stdio and Streamable HTTP transports, applying each of them directly in your own code.

On day one you use the official TypeScript or Python SDK to build an MCP server that exposes internal APIs, databases or files to AI assistants in a controlled way, and you test it with the MCP Inspector. Day two covers remote servers, OAuth-based authorisation, security risks such as prompt injection and tool poisoning, and operations, logging and governance in an enterprise setting. You learn to write tool descriptions that models use reliably, and you leave knowing how to integrate MCP servers safely into your development and agent landscape.

JavaScript and TypeScript now run in the browser, on servers, in build pipelines and on edge platforms. That breadth comes with complex toolchains: bundlers, transpilers, linters, package managers and an npm ecosystem that never stands still. AI coding assistants and agents remove a great deal of that friction. They migrate JavaScript modules to TypeScript incrementally, derive precise types from API responses, fix ESLint findings, write Vitest or Jest tests and explain nested generics in plain language. For the output to fit your project, the tools need clear guardrails: tsconfig strictness, module system, coding guidelines and test commands. This course shows you how to provide that context deliberately and how to scrutinise generated code.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • Front-end and full-stack developers working in JavaScript or TypeScript
  • Teams migrating an existing JavaScript codebase to TypeScript
  • Library and SDK maintainers in the npm ecosystem
  • Tech leads who own tooling, linting and build processes

Typical challenges we address

  • Gradual type erosion through any, type assertions and lax tsconfig settings
  • Complex toolchains mixing bundlers, transpilers, ESM and CommonJS that are hard to debug
  • Huge dependency trees carrying security and maintenance risk
  • Asynchronous code with hard-to-reproduce race conditions and gaps in error handling

What you will be able to do

  • You explain the MCP architecture and choose between tools, resources and prompts for each use case.
  • You develop your own MCP server in TypeScript or Python and test it systematically.
  • You connect MCP servers to Claude Code, Cursor, Copilot and custom agents.
  • You run remote servers using Streamable HTTP and OAuth-based authorisation.
  • Use AI agents deliberately for TypeScript migrations, typing work and test generation.
  • Feed assistants your tsconfig, lint rules and project conventions so generated code fits your existing stack.
  • Critically assess proposed npm dependencies and generated code for type safety and security.

Course outline

Day 1

Module 1 Architecture and core concepts
  • Roles of host, client and server and the lifecycle of a connection
  • JSON-RPC messages, capability negotiation and notifications
  • Tools, resources and prompts: choosing the right primitive
  • Client features such as sampling, roots and elicitation at a glance
Module 2 Building your own MCP server
  • Setting up a server with the official TypeScript or Python SDK
  • Defining tools cleanly with JSON Schema for inputs and outputs
  • Exposing resources and resource templates for documents, records and configuration
  • Testing and debugging with the MCP Inspector and meaningful error messages
Module 3 Connecting to Claude Code, Cursor, Copilot and agents
  • Configuring local stdio servers and remote servers in clients
  • Project-level and user-level configuration, approvals and permissions
  • Writing tool descriptions that models reliably select correctly
  • Integrating MCP servers into custom agents built with the Claude Agent SDK or OpenAI Agents SDK
Module 4 Transport, authorisation and operations
  • Streamable HTTP, session management and stateless servers
  • OAuth-based authorisation, token validation and integration with existing identity providers
  • Deploying as containers, on serverless platforms or behind a gateway
  • Logging, monitoring, rate limiting and versioning tool interfaces

Day 2

Module 5 Security and governance
  • Threats: prompt injection via tool results, tool poisoning, confused deputy
  • Least privilege, confirmation requirements and sandboxing
  • Reviewing and approving third-party servers within the organisation
  • Data protection, logging of personal data and requirements under GDPR and the EU AI Act
Module 6 Practice lab: JavaScript & TypeScript
  • Incremental TypeScript migration
  • Deriving types from APIs and schemas
  • Writing Vitest and Jest tests
  • Fixing ESLint findings and code smells
  • Debugging build and bundler issues
  • Upgrading dependencies
Module 7 Data protection, quality & transfer to daily work
  • The npm ecosystem is a frequent target of supply-chain attacks, so vet every dependency the AI suggests for provenance, maintenance and licence (for example copyleft terms). Keep API keys and tokens out of prompts and clarify contractually whether your source code may be used to train the provider’s models.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Incremental TypeScript migration

The agent converts JavaScript files to TypeScript module by module, infers types from usage, replaces any with precise types and tightens tsconfig strictness in controlled steps until the compiler runs clean.

Deriving types from APIs and schemas

JSON samples, OpenAPI specifications or database schemas are turned into TypeScript interfaces and Zod schemas for runtime validation, so front end and back end share one consistent contract.

Writing Vitest and Jest tests

For utilities, hooks and services, the AI generates unit tests with sensible mocks, fake timers and snapshot strategies, runs them and fixes failing cases on its own.

Fixing ESLint findings and code smells

The assistant works through lint warnings systematically, replaces outdated patterns such as callback chains with async/await and explains for each rule why the change makes sense.

Debugging build and bundler issues

Error output from Vite, webpack or esbuild is analysed, ESM/CommonJS conflicts are resolved and configuration for path aliases, tree shaking or source maps is corrected.

Upgrading dependencies

The AI reads changelogs for major npm package upgrades, adapts code to breaking changes, updates lockfiles and verifies everything through a type check and a full test run.

Possible hands-on projects

Type-safe API client

A small TypeScript package that generates a type-safe fetch client with Zod validation from an OpenAPI specification, ready to publish to npm with tests.

Browser extension

A TypeScript browser extension that analyses page content and copies it to the clipboard in a structured format – including manifest, content script and automated build.

Monorepo health check

A Node script that inspects workspaces in a monorepo, detects duplicate or inconsistent dependency versions and proposes a clean-up plan.

Prerequisites

Solid programming skills in TypeScript/JavaScript or Python and a basic understanding of HTTP APIs and JSON. Some experience using AI assistants in day-to-day development is helpful. Good command of modern JavaScript, a working knowledge of TypeScript and experience with npm, pnpm or yarn and Git.

Technical requirements

A laptop with Node.js or Python, Git and a code editor, plus access to at least one MCP-capable client such as Claude Code, Claude Desktop, Cursor or VS Code with Copilot.

Data protection & compliance

The npm ecosystem is a frequent target of supply-chain attacks, so vet every dependency the AI suggests for provenance, maintenance and licence (for example copyleft terms). Keep API keys and tokens out of prompts and clarify contractually whether your source code may be used to train the provider’s models.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Tue, 24 November 2026 – Wed, 25 November 2026 Online Request
  • Mon, 30 November 2026 – Tue, 1 December 2026 Hanover Request
  • Thu, 17 December 2026 – Fri, 18 December 2026 Online Request
  • Thu, 14 January 2027 – Fri, 15 January 2027 Online Request
  • Wed, 20 January 2027 – Thu, 21 January 2027 Munich Request
  • Mon, 1 February 2027 – Tue, 2 February 2027 Online Request

Frequently asked questions

Why would I need my own MCP server?

Whenever AI assistants need access to internal systems such as ticketing tools, databases, documentation or line-of-business applications. Your own server defines precisely which actions and data are available and can then be reused across several clients. That avoids isolated one-off integrations and keeps access firmly under your control.

Which programming language does the course use?

You can choose between TypeScript and Python, both of which have official SDKs. The concepts are identical and all exercises are available in both versions. Developers working in other languages still benefit, because the protocol is language-agnostic and SDKs for other languages follow a similar structure.

How secure is MCP for enterprise use?

The protocol provides mechanisms for authorisation and permissions, but real-world security depends on implementation and operations. Risks such as prompt injection through tool results or over-privileged servers are genuine. We cover concrete countermeasures, approval processes for third-party servers and how to handle personal data.

How well do AI assistants handle complex TypeScript types?

Current models understand generics, conditional types and mapped types very well and can explain them clearly. For highly complex type constructions, though, the compiler remains the ultimate judge. On the course you learn to have the agent run tsc iteratively, so suggestions are not merely plausible but genuinely type-correct before you accept them.

Is the course suitable for pure front-end developers?

Yes. The focus is the language and its tooling – typing, tests, linting, builds and dependencies – which matter equally on the front end and the back end. If you want to go deeper into React or Node.js specifically, our catalogue includes dedicated course variants for those stacks.

How much does “Model Context Protocol (MCP) for JavaScript and TypeScript Developers” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 2 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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