Training course · Model Context Protocol (MCP) · MVP Development for Startups

Model Context Protocol (MCP) for Startups and MVP Development

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 MVP Development for Startups. 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.

For founders and early product teams, speed determines how fast they learn from the market. AI coding tools, vibe coding and app builders now make it possible to turn an idea into a working minimum viable product with sign-up, database, payments and a landing page within days, often without a large engineering team. The real challenge shifts as a result: which hypothesis are you testing, which features truly belong in the MVP, and how does a quick prototype become a codebase that withstands investor due diligence, the first paying customers and growth? In this course you learn to build MVPs purposefully with AI agents, manage technical debt deliberately, build in security and data protection from day one and prepare the handover to a professional engineering team.

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?

  • Founders with little or no programming experience
  • Technical co-founders and first engineers in startups
  • Product managers in early-stage product teams
  • Corporate innovation and venture building teams
  • Participants in incubator and accelerator programmes

Typical challenges we address

  • Limited time and budget to validate a product idea in the market
  • Lack of engineering capacity or dependence on external agencies
  • Quickly built prototypes with security holes, open databases and unclear architecture
  • Uncertainty about when to rewrite an MVP and when to evolve it

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.
  • Turn a business idea into a focused MVP scope and build it yourself with AI tools.
  • Integrate sign-up, database, payments and analytics and check your MVP for common security gaps before launch.
  • Manage technical debt deliberately and prepare the codebase for growth, due diligence and an engineering team.

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: MVP Development for Startups
  • From pitch to specification
  • Building the MVP by prompt
  • Payments and integrations
  • Landing pages and experiments
  • Pre-launch security check
  • Making the codebase hand-over ready
Module 7 Data protection, quality & transfer to daily work
  • Even an MVP processes real customer data: you learn to implement GDPR essentials such as privacy notices, data processing agreements and consent, manage API keys and secrets securely and clarify licensing and copyright questions around generated code that become relevant in due diligence.
  • 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

From pitch to specification

Translate the business idea, target group and core hypothesis into user stories, a data model and a prioritised scope that stays deliberately small and includes measurable learning goals for the market test.

Building the MVP by prompt

Generate a web app with sign-up, database, core feature and admin area step by step using AI agents or app builders, working in small, tested iterations with the code under version control.

Payments and integrations

Integrate subscriptions and one-off payments through a payment provider, transactional email, analytics and first integrations, with webhooks, error handling and securely stored API keys. Test and live modes stay separate.

Landing pages and experiments

Create landing pages, waitlists and pricing pages in several variants, track conversion events and run quick A/B tests to check demand and willingness to pay before investing in heavier development.

Pre-launch security check

Have the MVP code checked for open database rules, missing access controls, exposed keys and unprotected endpoints, and work through a short checklist for a safe go-live.

Making the codebase hand-over ready

Document the architecture, add tests, refactor critical areas and produce a technical overview that new engineers or a technical due diligence can follow quickly. This also helps investor conversations.

Possible hands-on projects

Waitlist landing page

A landing page with value proposition, email capture, double opt-in and a simple dashboard that analyses sign-ups and traffic sources.

Booking MVP

A small web app where customers book and pay for appointments, providers manage availability and both sides receive email confirmations.

Interview synthesis tool

A tool that collects notes from customer interviews, clusters statements by problems and wishes and shows evidence for or against the core hypothesis.

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 have a concrete product idea or work in an early-stage product team; no programming skills are required, though a basic technical understanding helps.

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

Even an MVP processes real customer data: you learn to implement GDPR essentials such as privacy notices, data processing agreements and consent, manage API keys and secrets securely and clarify licensing and copyright questions around generated code that become relevant in due diligence.

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 Salzburg Request
  • Wed, 16 December 2026 – Thu, 17 December 2026 Online Request
  • Mon, 18 January 2027 – Tue, 19 January 2027 Bremen Request
  • Tue, 26 January 2027 – Wed, 27 January 2027 Online Request
  • Wed, 3 February 2027 – Thu, 4 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.

Can a non-technical founder really build an MVP alone?

For many business models, yes: web apps with sign-up, data storage, a core feature and payments can be built with AI tools without programming skills. What matters are clear requirements, small steps and systematic testing. Complex logic, high security demands or rapid growth will eventually call for engineering expertise. In the course you learn to recognise that point.

Will an AI-built MVP have to be rewritten later?

Not necessarily. If you use version control from the start, keep the data model understandable, test core features and separate configuration from code, an MVP can often evolve step by step. We show which early decisions make later rework easier and how to tell when starting afresh is the cheaper option.

How much does “Model Context Protocol (MCP) for Startups and MVP Development” 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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