Training course · Model Context Protocol (MCP) · Salesforce Development

Model Context Protocol (MCP) for Salesforce 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 Salesforce Developers” is designed for roles such as Salesforce developers working with Apex and Lightning Web Components, Salesforce architects and technical leads and Salesforce administrators who also develop and shows step by step how to use Model Context Protocol (MCP) productively, safely and transparently in Salesforce Development – 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.

Salesforce orgs grow over the years into complex platforms of Apex classes, triggers, flows, Lightning Web Components and integrations. AI coding assistants and agents help Salesforce developers write Apex and LWC faster, generate test classes with meaningful coverage, account for governor limits early and move sprawling trigger logic into clean frameworks. They support SOQL optimisation, metadata analysis and the migration from Process Builder and workflow rules to Flow. Because Salesforce code must be multi-tenant aware, bulkified and security-conscious, AI needs targeted context and clear rules. In this course you learn to combine AI tools with Salesforce CLI, scratch orgs and your DevOps pipeline while reliably respecting sharing rules, field-level security and platform limits.

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?

  • Salesforce developers working with Apex and Lightning Web Components
  • Salesforce architects and technical leads
  • Salesforce administrators who also develop
  • Integration developers building Salesforce interfaces
  • Salesforce consultancies and partner teams

Typical challenges we address

  • Governor limits, bulkification and trigger recursion cause hard-to-reproduce errors
  • Mandatory test coverage consumes a lot of time writing test classes
  • Mature orgs with overlapping triggers, flows and processes and no documentation
  • Security requirements such as CRUD and FLS checks and sharing are often forgotten in code

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.
  • Develop Apex and Lightning Web Components with AI support that are bulkified, secure and within limits.
  • Generate meaningful test classes and analyse org metadata systematically with AI agents.
  • Integrate AI tools with Salesforce CLI, scratch orgs and your deployment pipeline.

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: Salesforce Development
  • Writing bulkified Apex
  • Generating test classes
  • Building Lightning Web Components
  • Optimising SOQL and performance
  • Analysing org metadata
  • Preparing for security review
Module 7 Data protection, quality & transfer to daily work
  • Salesforce orgs hold customer and sales data: you learn to share only metadata and anonymised samples with AI services, protect credentials and connected app secrets, implement GDPR requirements for data retention and clarify licensing questions around generated code in AppExchange packages.
  • 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

Writing bulkified Apex

Generate trigger handlers, service classes and batch or queueable jobs that keep SOQL and DML out of loops, respect governor limits and apply patterns such as trigger frameworks consistently.

Generating test classes

Create meaningful Apex tests with test data factories, positive and negative cases, bulk scenarios and assertions that verify real logic rather than just coverage, including mocks for callouts.

Building Lightning Web Components

Develop LWC components with wire adapters, Apex controllers, Lightning Data Service and Jest tests, and migrate existing Aura components step by step. Accessibility and loading states are covered too.

Optimising SOQL and performance

Write selective queries, interpret Query Plan results, spot large data volume issues and propose alternatives such as custom indexes, skinny tables or asynchronous processing. This prevents timeouts as data grows.

Analysing org metadata

Evaluate retrieved metadata to document automations per object, dependencies between fields, flows and Apex, and unused components, and plan clean-up work. The result is finally up-to-date documentation.

Preparing for security review

Examine Apex and LWC for missing CRUD and FLS checks, SOQL injection, unsafe sharing settings and cross-site scripting, and implement fixes using user mode and stripInaccessible.

Possible hands-on projects

Automation map

A script that reads an org’s metadata and shows every trigger, flow and validation rule per object, including execution order, in one overview.

Test data factory generator

A tool that produces a reusable Apex factory from object and field definitions, with required fields and valid picklist values.

LWC dashboard component

A Lightning Web Component that aggregates an account’s key figures from several objects and displays them with filters and drill-down.

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 already develop in Apex or Lightning Web Components and have a working knowledge of the Salesforce data model, governor limits and Salesforce CLI.

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

Salesforce orgs hold customer and sales data: you learn to share only metadata and anonymised samples with AI services, protect credentials and connected app secrets, implement GDPR requirements for data retention and clarify licensing questions around generated code in AppExchange packages.

Suggested dates

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

  • Tue, 24 November 2026 – Wed, 25 November 2026 Online Request
  • Tue, 1 December 2026 – Wed, 2 December 2026 Hanover Request
  • Tue, 15 December 2026 – Wed, 16 December 2026 Online Request
  • Mon, 18 January 2027 – Tue, 19 January 2027 Online Request
  • Tue, 2 February 2027 – Wed, 3 February 2027 Stuttgart Request
  • Tue, 16 February 2027 – Wed, 17 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.

How well do general-purpose AI assistants know Apex and Salesforce specifics?

Current models handle Apex syntax and common patterns well. Weaknesses show up around governor limits, bulkification and org-specific objects. With rule files covering your trigger framework, naming conventions and security standards, plus retrieved metadata as context, results become far more reliable. In the course you build exactly this context for your org.

Should an AI agent deploy straight into our Salesforce org?

We recommend letting agents work in scratch orgs or sandboxes and promoting changes to higher environments through version control and your deployment pipeline. That preserves reviews, test runs and approvals. Production orgs should be reachable by agents read-only at most, using a restricted user. You practise this way of working hands-on in the course.

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