MCP Fundamentals for Engineers
Master the Model Context Protocol (MCP). Build standard servers and clients from scratch and solve the M×N integration nightmare once and for all.
What You Will Learn
- ✓Understand the M×N integration problem and how MCP solves it
- ✓Build MCP servers with tools, resources, and prompts using FastMCP
- ✓Build MCP clients that auto-discover server capabilities
- ✓Connect LLM-powered chat UIs to MCP servers
- ✓Design multi-server architectures with config-driven routing
Who Is This For
- AI engineers who You are writing the same tool schemas and dispatchers for every new integration. There has to be a better way.
- Backend developers who You want to expose your APIs to AI apps but do not want to maintain custom integrations for each one.
- Technical leads who Your team is building AI features and you need a standard protocol instead of custom glue code everywhere.
Curriculum
Why MCP exists
3 lessons
MCP architecture
3 lessons
Feel the pain
3 lessons
Your first MCP Server
3 lessons
The complete picture
3 lessons
Multi-server architecture
3 lessons
Frequently Asked Questions
- Do I need to know LangChain?
- No. We use pure Python and LiteLLM. No frameworks.
- What LLM provider do I need?
- Any provider that supports function calling. LiteLLM handles OpenAI, Anthropic, Google AI Studio (free tier), and more.
- Should I take Building AI Agents first?
- Yes. This workshop assumes you understand tool calling and agent loops. Building AI Agents covers those foundations.
- How long does the workshop take?
- About 7 hours. Most people finish in 2 sessions over a weekend.
MCP Fundamentals for Engineers
Master the Model Context Protocol (MCP). Build standard servers and clients from scratch and solve the M×N integration nightmare once and for all.
Chosen by engineers at forward-thinking AI companies
The integration nightmare. Which one sounds familiar?
The m×n explosion
3 AI apps and 5 data sources means you are maintaining 15 custom API integrations. It is completely unscalable.
Duplicate tool schemas
You rewrite the exact same JSON schema for your internal database in LangChain, then in AutoGen, then in your custom agent.
Fragile dispatchers
Every time an API changes, you have to find and update 4 different agent dispatchers. When one breaks, the whole agent fails.
Hardcoded prompts
You are stuffing database connection instructions directly into your LLM system prompt because you do not know how to decouple them.
The fix isn't a better agent framework.
It's a standardized protocol.
Senior engineers aren't better because they know more syntax. They're better because they've:
MCP is the USB-C of AI integrations. Build it once, use it everywhere.
Stop hardcoding integrations.
Start exposing capabilities.
We teach you the foundational specification of MCP. You will build servers that expose tools and clients that dynamically discover and call them. Zero boilerplate.
The protocol mastery path
From the M×N problem to an elegant multi-server architecture.
Feel the pain
You experience the M×N integration problem firsthand by building custom glue code so you understand exactly what MCP solves.
The first Server
You build an MCP server exposing Tools and Resources securely to any compliant client using FastMCP.
The client architecture
You build an MCP client that automatically negotiates capabilities and manages context dynamically.
Multi-server routing
You architect a master router client that multiplexes queries across dozens of independent MCP servers.
From Zero Integrations to Multi-server MCP.
Why MCP exists
Understand the integration nightmare that MCP solves. See the M×N problem, feel the pain, and discover the protocol that fixes it.
Welcome & setup
Get introduced to the workshop, meet the DevTools AI Assistant storyline, and set up your environment.
The m×n problem
See how AI integrations explode in complexity. Three apps times five data sources equals fifteen custom integrations.
MCP: usb for AI
Discover the Model Context Protocol and how it turns M×N into M+N and why it is the USB-C of AI integrations.
MCP architecture
Learn the three roles (Host, Client, Server), three capabilities (Tools, Resources, Prompts), and transport protocols that make MCP work.
Three roles: host, client, Server
Understand the three participants in every MCP interaction and how they work together.
Three capabilities: tools, resources, prompts
Learn what MCP servers can expose: tools for actions, resources for data, and prompts for workflows.
Transport & protocol
Learn the three MCP transport options (STDIO, SSE, and Streamable HTTP) and how to switch between them with one line of code.
Feel the pain
Build tool integrations the manual way with hand-written schemas, dispatchers, and glue code. Feel the boilerplate so the MCP relief hits harder.
Manual arxiv integration
Build an arXiv search integration the hard way with tool functions, hand-written JSON schemas, name-to-function mapping, and a dispatcher.
Manual wikipedia integration
Build a second integration and feel the deja vu. Same boilerplate, different API.
The duplication tax
Compare both integrations side-by-side and see the full cost of manual tool wiring.
Your first MCP Server
Build an MCP server with FastMCP, test it with the MCP Inspector, and connect your first client. Watch the boilerplate vanish.
FastMCP & @mcp.tool()
Create an MCP server in two lines, add tools with a decorator, and watch JSON schemas auto-generate.
Testing with MCP inspector
Run your server, test tools with the MCP Inspector, and verify everything works.
Your first MCP client
Build an MCP client that connects, discovers tools, and calls them, all with zero schema definitions.
The complete picture
Build a full chat client with LLM integration, add MCP resources for read-only data, and prompts for workflow templates.
Full chat client with LLM
Build a Streamlit chat UI that connects to your MCP server with LLM-powered tool calling.
MCP resources
Add read-only data endpoints to your server with @mcp.resource(), covering static and templated URIs.
MCP prompts
Add workflow templates to your server with @mcp.prompt() and build a complete server with all three capabilities.
Multi-server architecture
Connect to multiple MCP servers simultaneously. Add new data sources with a single line in a config file.
Config-driven Server management
Use a JSON config file to manage multiple MCP servers. Add or remove data sources without changing code.
Tool routing across servers
Build the multi-server client that connects, discovers, and routes tool calls across multiple servers.
Production patterns & what's Next
Speed round on MCP concepts, design your own MCP architecture, and celebrate completing the workshop.
Start learning for free
Create your free account and start building.
Amateurs write glue code. Professionals build protocols.
APIs are easy.
Anyone can write a `grequests.get()` and dump it into an LLM context window.
Architecture is hard:
- Design universally accepted tool schemas
- Implement standardized capability negotiation
- Secure multi-transport execution boundaries
- Architect dynamic context hydration systems
Stop writing one-off integrations. Start building infrastructure.
Learn From Someone Who Actually Does This
I am the Cofounder of AEOsome.com and Chief Mentor at learnwithparam.com, with 15+ years of software engineering experience building production systems.
"Most engineers are not blocked by ability, but by lack of real system ownership."
Guest Sessions From Engineers at
Live sessions on System Design, Career Growth, and Interview Preparation.
Ready to Start Learning?
This entire course is free. No credit card required. Enroll and start building.
Frequently Asked Questions
Do I need to know LangChain?
What LLM provider do I need?
Should I take Building AI Agents first?
How long does the workshop take?
7 hours from now:
Stop repeating yourself. Start building protocols.