LOCKEDIN / FORWARD-DEPLOYED ENGINEERING 101
Understand it.
Then build it.
You can be an experienced engineer and still be new to agents. Start with what each thing is and how it helps a person do useful work. Explore 48 original introductions across software, agents, cloud, security and delivery. Start here without a model key; each topic connects to deeper instruction and practice.
- 101UnderstandPlain language, visual walkthrough, vocabulary
- 102Build with guidanceOriginal lessons, examples and knowledge checks
- 103Practise and explainRunnable labs, failure cases and handover
- 01Discover the tool
- 02Request a lookup
- 03Return the result
An open protocol for connecting AI applications to tools and data
What is MCP?
MCP means Model Context Protocol. It defines a common way for an AI application to discover and use capabilities supplied by another program, such as reading a document or looking up a ticket. It is a communication protocol, not an AI model, a programming language or a workflow builder by itself.
An FDE needs to connect AI software to the systems where work happens. MCP can standardize that connection, while the receiving system still checks identity, permissions and the requested inputs.
CONNECT IT TO WHAT YOU KNOW
Start with something familiar.
A common wire protocol lets different clients and servers understand the same kinds of messages. MCP provides that shared contract for capabilities exposed to AI applications.
MCP is a protocol. An MCP SDK is code for implementing it; an MCP server is a program exposing capabilities. None of these is itself a model or permission to perform every available action.
Words worth knowing
- Protocol
- Agreed rules for how programs exchange messages.
- Client
- The connecting component inside the AI application.
- Server
- The program that offers tools, resources or prompts through MCP.
- SDK
- A software development kit: code that helps you implement the protocol.
ONE EXAMPLE / FICTIONAL CASE
Watch the work take shape.
Instead of wiring a different ticket-lookup interface into every assistant, expose a small lookup through an MCP server. The assistant's MCP client discovers the tool and requests a call. The server decides what this caller is allowed to read.
- 01Discover the tool
- 02Request a lookup
- 03Return the result
Discover the tool
The AI application connects through an MCP client. The MCP server describes the available lookup and its accepted inputs.
A tool description the application can inspectFROM RECOGNITION TO REASONING
Describe one MCP tool without granting broad authority.
- 01
Name a read-only procedure lookup and its input shape.
- 02
Identify the client, server and underlying data service.
- 03
Write the authorization check and one rejected call.
A client-to-server diagram and a tool contract.
Compare your reasoning when you are ready
Discovering a tool establishes that it exists. The server must still validate its arguments and authorize the caller before accessing the underlying service.
Keep notes in your own working copy. Moving through these cards does not record completion.
TURN THE IDEA INTO USEFUL WORK
You can now go deeper.
MCP connects capabilities. LangGraph coordinates steps. LangChain helps assemble agents. These are different jobs and can be used together.
Academy lessons use your existing training access. Free guides stay open.
Learn with the original creators
Begin with Introducing MCP and MCP clients, then return to our local SDK lab. The provider course includes its own exercises.