Training course · Model Context Protocol (MCP) · React & Front End

Model Context Protocol (MCP) for React and Front-End 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 React and Front-End Developers” is designed for roles such as React developers in product teams and agencies, Front-end engineers working with Next.js, Vite or similar frameworks and Maintainers of design systems and component libraries and shows step by step how to use Model Context Protocol (MCP) productively, safely and transparently in React & Front End – from the fundamentals to advanced workflows.

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.

Front-end development today means component architectures, state management, server components, design systems, accessibility and performance budgets – often all at once. AI coding assistants and agents speed up exactly the work that eats time: deriving components from designs, converting class components to hooks, writing Storybook stories and Testing Library tests, fixing ARIA issues or tracking down unnecessary re-renders. Because front-end code thrives on conventions, context is everything: design tokens, folder structure, styling approach and preferred libraries must be known to the assistant. This course shows you how to set those guardrails and how to verify results reliably, both visually and technically.

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?

  • React developers in product teams and agencies
  • Front-end engineers working with Next.js, Vite or similar frameworks
  • Maintainers of design systems and component libraries
  • Full-stack developers with a front-end focus
  • UI engineers responsible for accessibility and performance

Typical challenges we address

  • Inconsistent components and styles despite an existing design system
  • Hard-to-trace re-renders, bloated bundles and weak Core Web Vitals
  • Accessibility gaps and growing pressure from legal requirements
  • Legacy code with class components, outdated patterns and missing tests

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.
  • Have AI agents generate components, stories and tests that match your design system.
  • Use AI deliberately to improve accessibility, performance and legacy code in a systematic way.
  • Check generated front-end code visually, functionally and for maintainability before it ships.

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: React & Front End
  • Building components from designs
  • Testing Library tests
  • Auditing and improving accessibility
  • Modernising legacy code
  • Optimising performance
  • Forms and data fetching
Module 7 Data protection, quality & transfer to daily work
  • Under the European Accessibility Act and its national implementations, many digital services must be accessible, so generated UI code needs proper checks. Also watch the licences of reused components and icons, keep secrets out of the client bundle and make sure tracking and consent logic complies with GDPR and ePrivacy rules.
  • 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

Building components from designs

From screenshots, design specs or Figma exports, the assistant produces typed React components that use your existing design tokens and libraries, and adds Storybook stories covering every state.

Testing Library tests

The AI writes user-centred component tests with React Testing Library and Vitest or Jest, simulates interactions, mocks API calls and covers loading, error and empty states.

Auditing and improving accessibility

The agent reviews components for semantic HTML, ARIA attributes, focus management and contrast, interprets axe results and fixes findings transparently against WCAG success criteria. Keyboard and screen reader behaviour is covered too.

Modernising legacy code

Class components are converted to function components with hooks, prop drilling is replaced by context or a proper state management approach and PropTypes give way to TypeScript types – with tests as a safety net.

Optimising performance

The AI pinpoints unnecessary re-renders, proposes memoisation, code splitting and lazy loading, analyses bundle reports and explains how each measure affects metrics such as LCP and INP.

Forms and data fetching

Complex forms with validation schemas, error messages and optimistic updates are generated alongside data-fetching logic with caching, retries and clean handling of loading and error states.

Possible hands-on projects

Interactive KPI dashboard

A React dashboard with charts, filters and a responsive layout that loads data from a REST API, built entirely by an AI agent from a short specification.

Component library with Storybook

A small, accessible component library with buttons, dialogs and form fields, including design tokens, Storybook documentation and automated tests. It forms the basis for consistent interfaces across several projects.

Accessibility checker for pull requests

A script that runs axe against Storybook stories automatically and turns the findings into a clear report attached to pull requests.

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. Hands-on experience with React and modern JavaScript or TypeScript, plus a working knowledge of CSS, npm 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

Under the European Accessibility Act and its national implementations, many digital services must be accessible, so generated UI code needs proper checks. Also watch the licences of reused components and icons, keep secrets out of the client bundle and make sure tracking and consent logic complies with GDPR and ePrivacy rules.

Suggested dates

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

  • Thu, 26 November 2026 – Fri, 27 November 2026 Online Request
  • Thu, 10 December 2026 – Fri, 11 December 2026 Stuttgart Request
  • Thu, 14 January 2027 – Fri, 15 January 2027 Online Request
  • Wed, 27 January 2027 – Thu, 28 January 2027 Berlin Request
  • Mon, 1 February 2027 – Tue, 2 February 2027 Online Request
  • Wed, 17 February 2027 – Thu, 18 February 2027 Munich 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.

Can AI implement designs pixel-perfectly?

AI assistants now translate layouts from screenshots or specs remarkably well, especially when they know your design tokens and components. Pixel-perfect results still come from iteration, though. On the course you learn to feed back visual deviations precisely and to use Storybook and visual tests as your control mechanism.

Does the framework I use matter?

The course centres on React, but the working methods transfer to Next.js, Remix or Vite-based setups. We show how to capture framework-specific rules such as server and client components or routing conventions in instruction files, so the assistant produces code that fits your stack.

How much does “Model Context Protocol (MCP) for React and Front-End 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.

More courses for React and Front-End Developers

More Model Context Protocol (MCP) courses

All 29 Model Context Protocol (MCP) courses

Model Context Protocol (MCP) · MunichModel Context Protocol (MCP) · SalzburgModel Context Protocol (MCP) · BerlinModel Context Protocol (MCP) · AugsburgModel Context Protocol (MCP) · HanoverModel Context Protocol (MCP) · BremenModel Context Protocol (MCP) · StuttgartModel Context Protocol (MCP) · KaiserslauternModel Context Protocol (MCP) · Online