Training course · Model Context Protocol (MCP) · Rust

Model Context Protocol (MCP) for Rust 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 Rust Developers” is a hands-on course for roles such as Rust developers working on systems and back-end projects, C and C++ developers moving to Rust or porting modules and Embedded and IoT developers using Rust. Rather than learning Model Context Protocol (MCP) in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Rust.

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.

Rust is gaining ground wherever memory safety and performance have to go hand in hand: in systems software, embedded projects, network services, WebAssembly and security-critical components. The learning curve is steep – ownership, lifetimes, traits and async runtimes challenge even experienced developers. AI coding assistants and agents prove to be patient sparring partners here: they explain borrow checker errors, suggest suitable ownership structures, write tests and property-based tests, port C or C++ modules incrementally and work through Clippy lints. Because the compiler gives very precise feedback, agents can iterate all the way to compiling, safe code. This course teaches you to exploit that feedback loop and to scrutinise unsafe code with particular care.

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?

  • Rust developers working on systems and back-end projects
  • C and C++ developers moving to Rust or porting modules
  • Embedded and IoT developers using Rust
  • Security and platform teams focused on memory safety

Typical challenges we address

  • Hard-to-understand borrow checker and lifetime errors
  • Complex trait hierarchies, generics and async code with Tokio
  • Laborious porting of existing C or C++ codebases across FFI boundaries
  • Handling unsafe blocks responsibly and justifying each one

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 as sparring partners for ownership, lifetimes, traits and async Rust.
  • Generate tests, ports and services and verify them with the compiler, Clippy and Miri.
  • Systematically assess generated unsafe and FFI code for memory safety.

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: Rust
  • Understanding and fixing compiler errors
  • Tests and property-based tests
  • Porting C and C++ modules
  • Async services with Tokio
  • Clippy and idiomatic code
  • Reviewing unsafe code
Module 7 Data protection, quality & transfer to daily work
  • Rust is often used in security-critical components for which the Cyber Resilience Act sets requirements on vulnerability handling and SBOMs. Check new crates for vulnerabilities and licences with cargo-audit or cargo-deny, and treat proprietary systems code as confidential when using cloud-hosted 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

Understanding and fixing compiler errors

The assistant explains borrow checker and lifetime errors in plain language, deliberately proposes alternative ownership structures such as references, Rc or cloning, and iterates with cargo check until the build is clean.

Tests and property-based tests

The AI writes unit and integration tests, doc tests and property-based tests with proptest that check invariants over many generated inputs, uncovering edge cases in parsers or algorithms.

Porting C and C++ modules

Existing code is moved to Rust module by module, FFI bindings are created with bindgen or cbindgen and behaviour is safeguarded by shared tests run against the old and new implementations.

Async services with Tokio

Specifications become HTTP or gRPC services built with Axum or Tonic, including structured error types, graceful shutdown, tracing and sensible handling of cancellation and timeouts.

Clippy and idiomatic code

Clippy lints are worked through systematically, error handling standardised with thiserror or anyhow, and iterators, pattern matching and traits used idiomatically. Existing tests safeguard every change.

Reviewing unsafe code

The agent inventories unsafe blocks, documents their safety invariants, proposes safe alternatives and runs Miri to detect undefined behaviour. Each justification is recorded as a SAFETY comment in the code.

Possible hands-on projects

Fast log parser

A Rust CLI that streams large log files, detects patterns with regular expressions and outputs statistics – with benchmarks comparing it against a scripting-language version.

Axum microservice

A small REST service using Axum, SQLx, structured tracing and integration tests, planned and implemented end to end by an AI agent.

WebAssembly module

A compute-heavy function, such as image processing or validation, packaged as a WebAssembly module with wasm-bindgen and embedded in a simple web page.

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. Basic Rust experience with Cargo, ownership and traits, plus experience in at least one other systems or back-end language.

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

Rust is often used in security-critical components for which the Cyber Resilience Act sets requirements on vulnerability handling and SBOMs. Check new crates for vulnerabilities and licences with cargo-audit or cargo-deny, and treat proprietary systems code as confidential when using cloud-hosted models.

Suggested dates

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

  • Mon, 23 November 2026 – Tue, 24 November 2026 Online Request
  • Tue, 1 December 2026 – Wed, 2 December 2026 Kaiserslautern Request
  • Wed, 9 December 2026 – Thu, 10 December 2026 Online Request
  • Tue, 15 December 2026 – Wed, 16 December 2026 Bremen Request
  • Thu, 7 January 2027 – Fri, 8 January 2027 Online Request
  • Tue, 12 January 2027 – Wed, 13 January 2027 Salzburg 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 help me get started with Rust?

Very much so. AI assistants explain compiler errors patiently and in the context of your own code, show alternative approaches and explain why the borrow checker rejects a construct. The key is to understand the explanations rather than accept suggestions blindly, so the course relies on hands-on exercises in which you work out solutions together with the AI.

How reliable are AI ports from C++ to Rust?

They work well for clearly bounded modules when behaviour is protected by tests. The tricky parts are pointer arithmetic, shared mutable state or undefined behaviour in the original. On the course you learn to port incrementally, run differential tests against the old implementation and keep unsafe code to a deliberate minimum.

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