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Part of the bootcamp
MCP Fundamentals for Engineers is one workshop inside AI Bootcamp for Software Engineers.
See the full path with mentor reviews and a portfolio outcome.
Master the Model Context Protocol (MCP). Build standard servers and clients from scratch and solve the M×N integration nightmare once and for all.
Engineers are learning here from
Every new AI integration means more glue code: schemas, dispatchers, parsers. MCP fixes this. Build MCP servers and clients from scratch: tools, resources, prompts, multi-server routing. Go from 200 lines of boilerplate per integration to zero.
Build MCP servers and clients from scratch. No more glue code.
What you'll ship
What you'll learn
Curriculum
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.
MCP architecture
Learn the three roles (Host, Client, Server), three capabilities (Tools, Resources, Prompts), and transport protocols that make MCP work.
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.
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.
The complete picture
Build a full chat client with LLM integration, add MCP resources for read-only data, and prompts for workflow templates.
Multi-server architecture
Connect to multiple MCP servers simultaneously. Add new data sources with a single line in a config file.
Who it's for
You are writing the same tool schemas and dispatchers for every new integration. There has to be a better way.
You want to expose your APIs to AI apps but do not want to maintain custom integrations for each one.
Your team is building AI features and you need a standard protocol instead of custom glue code everywhere.
FAQ
No. We use pure Python and LiteLLM. No frameworks.
Any provider that supports function calling. LiteLLM handles OpenAI, Anthropic, Google AI Studio (free tier), and more.
Yes. This workshop assumes you understand tool calling and agent loops. Building AI Agents covers those foundations.
About 7 hours. Most people finish in 2 sessions over a weekend.
Build MCP servers and clients from scratch. No more glue code.