Training course · Model Context Protocol (MCP) · Mobile Apps

Model Context Protocol (MCP) for Mobile 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

This course connects Model Context Protocol (MCP) with the everyday processes of Mobile Apps. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

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.

Mobile development spans several worlds: Swift and SwiftUI for iOS, Kotlin and Jetpack Compose for Android, and cross-platform approaches with Flutter or React Native. On top come store guidelines, device fragmentation, offline capability, push notifications and demanding release processes. AI coding assistants and agents relieve teams of precisely these tasks: they build screens from designs, migrate UIKit or XML layouts to declarative UI frameworks, write UI and unit tests, analyse crash reports and automate build pipelines with Fastlane. Because mobile projects depend heavily on platform conventions, the AI needs precise context on architecture, state management and target platforms. This course shows you how to build that context and verify results on real devices.

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?

  • iOS developers using Swift and SwiftUI
  • Android developers using Kotlin and Jetpack Compose
  • Cross-platform developers using Flutter or React Native
  • Mobile teams in agencies and product companies
  • Tech leads responsible for app architecture and releases

Typical challenges we address

  • Maintaining several platforms in parallel with different languages and UI paradigms
  • Migrating from UIKit or XML layouts to declarative UI frameworks
  • Hard-to-reproduce crashes and performance issues across a wide range of devices
  • Laborious build, signing and store release processes

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 for screens, UI migrations and tests in native and cross-platform apps.
  • Diagnose crashes and performance issues faster and automate build and release processes with AI support.
  • Give the AI clear platform conventions and architecture rules and verify results on real devices.

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: Mobile Apps
  • Turning designs into screens
  • Declarative UI migration
  • Testing mobile apps
  • Analysing crash reports
  • Offline capability and data storage
  • Build and release automation
Module 7 Data protection, quality & transfer to daily work
  • Apps often handle sensitive device data such as location, contacts or health information, so generated code must request permissions sparingly and manage consent in line with GDPR. Signing keys, API keys and store credentials do not belong in prompts, and new SDKs and packages should be checked for licensing, tracking behaviour and supply-chain risk.
  • 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

Turning designs into screens

From screenshots or design specs, the assistant generates SwiftUI, Compose, Flutter or React Native screens that reuse your components, themes and navigation and respect dark mode and dynamic type.

Declarative UI migration

The agent moves UIKit view controllers or Android XML layouts to SwiftUI or Jetpack Compose step by step, wraps legacy parts via interop layers and protects behaviour with snapshot and UI tests.

Testing mobile apps

The AI writes unit tests for view models and repositories, UI tests with XCTest, Espresso or Flutter widget tests, and sets up mocks for networking and persistence.

Analysing crash reports

Symbolicated stack traces from crash reporting services are interpreted, likely causes such as threading or lifecycle issues narrowed down and fixes proposed alongside reproducing tests.

Offline capability and data storage

The assistant designs local persistence with Room, Core Data, SwiftData or SQLite, sync logic with conflict handling and robust networking layers with retries and caching.

Build and release automation

Fastlane lanes, Gradle configuration and CI workflows for builds, signing, beta distribution and store uploads are created or repaired, including versioning and release notes. Expiring certificates are flagged early.

Possible hands-on projects

Stocktake app with barcode scanner

A Flutter or React Native app that scans barcodes, records items offline and syncs them with a REST API once a connection is available.

SwiftUI habit tracker

An iOS app with SwiftUI, local persistence, widgets and local notifications, developed entirely with an AI agent. Habits and progress are displayed in clear charts.

Compose feedback form

An Android app built with Jetpack Compose that captures forms with photo attachments, caches them offline and submits them to a back end – with UI tests.

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 app development experience with Swift, Kotlin, Dart or React Native, plus Xcode or Android Studio 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

Apps often handle sensitive device data such as location, contacts or health information, so generated code must request permissions sparingly and manage consent in line with GDPR. Signing keys, API keys and store credentials do not belong in prompts, and new SDKs and packages should be checked for licensing, tracking behaviour and supply-chain risk.

Suggested dates

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

  • Wed, 25 November 2026 – Thu, 26 November 2026 Online Request
  • Wed, 9 December 2026 – Thu, 10 December 2026 Bremen Request
  • Thu, 7 January 2027 – Fri, 8 January 2027 Augsburg Request
  • Thu, 14 January 2027 – Fri, 15 January 2027 Online Request
  • Thu, 21 January 2027 – Fri, 22 January 2027 Salzburg Request
  • Thu, 4 February 2027 – Fri, 5 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.

Does the course cover iOS, Android and cross-platform equally?

Yes. Working with AI assistants follows the same principles on every platform: provide context, scope tasks and test the results. In the exercises you choose your focus – Swift, Kotlin, Flutter or React Native – and tackle typical tasks for your platform, so mixed teams benefit just as much as specialists.

Can AI work with Xcode and Android Studio?

Many AI assistants can be used inside Android Studio or alongside Xcode, and agents also work from the command line with xcodebuild, Gradle or the Flutter CLI. We show you how to drive builds, tests and simulators so that the agent can check its own results and fix errors iteratively.

How much does “Model Context Protocol (MCP) for Mobile 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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