Training course · Model Context Protocol (MCP) · C/C++ & Embedded

Model Context Protocol (MCP) for C/C++ and Embedded 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 C/C++ and Embedded Developers” is designed for roles such as Embedded software engineers working with microcontrollers and RTOS-based systems, C++ developers in systems software, automotive and industrial automation and Firmware and device driver developers and shows step by step how to use Model Context Protocol (MCP) productively, safely and transparently in C/C++ & Embedded – 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.

In embedded and systems development, determinism, memory safety and tight resource budgets matter more than almost anywhere else. AI coding assistants and agents help you read datasheets and register maps, write drivers and hardware abstraction layers, clear compiler warnings and static analysis findings, and build unit tests with mocks for hardware access. The domain also demands particular care: undefined behaviour, race conditions in interrupt handlers or MISRA violations creep in quickly when generated code is accepted uncritically. In this course you learn to integrate AI into your cross-compilation workflow with CMake, debuggers and hardware-in-the-loop tests while meeting the quality and safety expectations of functionally safe products.

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?

  • Embedded software engineers working with microcontrollers and RTOS-based systems
  • C++ developers in systems software, automotive and industrial automation
  • Firmware and device driver developers
  • Embedded Linux and Yocto developers
  • Test and verification engineers for embedded systems

Typical challenges we address

  • Memory errors, undefined behaviour and concurrency bugs are hard to find and costly in the field
  • Legacy C codebases full of global state and macros with little test coverage
  • Significant effort to comply with and evidence coding standards such as MISRA C/C++ or AUTOSAR C++
  • Hardware knowledge locked in datasheets and in the heads of a few experts

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.
  • Apply AI agents to driver development, refactoring and debugging in C and C++ in a targeted, verifiable way.
  • Raise test coverage of low-level software with generated unit tests and mocks that run on the host.
  • Combine AI support with coding standards, static analysis and the evidence requirements of safety-related development.

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: C/C++ & Embedded
  • Drivers from datasheets
  • Making sense of static analysis
  • Unit tests with hardware mocks
  • Crash and memory analysis
  • Introducing modern C++
  • Build and toolchain upkeep
Module 7 Data protection, quality & transfer to daily work
  • Firmware is often core intellectual property and may be subject to export control or security requirements: you learn how to protect source code, assess licensing risks in generated code and reconcile AI use with the Cyber Resilience Act, IEC 62443 and functional safety under ISO 26262 or IEC 61508.
  • 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

Drivers from datasheets

Have register descriptions and timing diagrams structured from datasheets, then derive headers with bitfield definitions, initialisation routines and a lean hardware abstraction layer for SPI, I²C or UART peripherals.

Making sense of static analysis

Explain and prioritise findings from clang-tidy, cppcheck or MISRA checkers, propose compliant corrections and prepare justified deviations for your deviation records. Recurring patterns can then be fixed across the codebase.

Unit tests with hardware mocks

Extract testable interfaces from low-level code, generate mocks for register and HAL access and create unit tests with GoogleTest, Unity or CppUTest that run on the host.

Crash and memory analysis

Interpret HardFault registers, stack traces, core dumps and sanitiser output, narrow down likely causes such as stack overflows or use-after-free and suggest targeted debugging steps.

Introducing modern C++

Gradually replace raw pointers, manual memory management and macros with RAII, constexpr, smart pointers and type-safe abstractions without degrading real-time behaviour or the memory budget.

Build and toolchain upkeep

Structure CMake projects for cross-compilation, create toolchain files, linker scripts and CI jobs for firmware builds and analyse build failures in the context of the target platform.

Possible hands-on projects

Register header generator

A script that converts register tables from an SVD or CSV file into type-safe C headers with masks, offsets and accessor functions.

Serial protocol monitor

A desktop tool that reads from a serial port, decodes a custom binary protocol and displays frames with timestamps and filters.

MISRA report dashboard

A small web view that aggregates static analysis results, groups rule violations by module and tracks progress across builds. New violations are highlighted.

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. You are proficient in C or C++ and experienced with build systems, debugging and low-level or systems programming.

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

Firmware is often core intellectual property and may be subject to export control or security requirements: you learn how to protect source code, assess licensing risks in generated code and reconcile AI use with the Cyber Resilience Act, IEC 62443 and functional safety under ISO 26262 or IEC 61508.

Suggested dates

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

  • Wed, 25 November 2026 – Thu, 26 November 2026 Online Request
  • Tue, 8 December 2026 – Wed, 9 December 2026 Salzburg Request
  • Thu, 17 December 2026 – Fri, 18 December 2026 Online Request
  • Mon, 11 January 2027 – Tue, 12 January 2027 Bremen Request
  • Thu, 28 January 2027 – Fri, 29 January 2027 Online Request
  • Thu, 4 February 2027 – Fri, 5 February 2027 Augsburg 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.

Is AI-generated code acceptable in safety-critical embedded systems?

Standards such as ISO 26262 or IEC 61508 do not prohibit AI tools, but they require traceable processes, reviews, testing and, where relevant, tool qualification. Generated code is therefore treated like any other code: reviewed, tested and verified against coding standards. In the course you develop working practices that support this evidence rather than bypass it.

Can an AI agent work with my target hardware?

Agents can trigger builds, flash devices, read serial output and run tests on the host or a hardware-in-the-loop rig, provided you expose the right command-line tools. We show you how to set up such loops in a controlled way, with clear permissions and without the agent accessing production devices unsupervised.

How much does “Model Context Protocol (MCP) for C/C++ and Embedded 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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