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Catalog / All levels / Model Context Protocol in LLM Production - Scalable Server Deployment
Mammoth Club All levels 7 sections 29 lectures

Model Context Protocol in LLM Production - Scalable Server Deployment

Getting an LLM working is one thing. Getting it to work reliably at scale in production is a different challenge entirely.

MC
Created by Team Mammoth
01
Skill level
All levels
02
Sections
7
03
Lectures
29
04
Instructor
Team Mammoth
What's inside

This course includes.

✓
7
Sections
✓
29
Lectures
✓
6
Resources
✓
1
Quizzes
✓
Certificate of completion
Included
✓
Mobile and desktop access
Included
✓
AI learning assistance
Included
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Course content

Curriculum & lectures.

6 sections · 28 lectures
+ 01 Foundations 5 lectures
01 What is MCP Locked
02 JSON-RPC 2.0 primer Locked
03 MCP lifecycle Locked
04 Core MCP primitives overview Locked
05 Module 1 Conclusion Locked
+ 02 Building MCP Servers 6 lectures
01 Setting up an MCP server (Python SDK) Locked
02 Defining and registering Tool functions with input schemas Locked
03 Returning structured tool results Locked
04 Adding server-side logging Locked
05 Sending progress notifications for long-running tools Locked
06 Module 2 Conclusion Locked
+ 03 Transports 4 lectures
01 stdio transport Locked
02 HTTP transport Locked
03 Choosing the right transport for your use case Locked
04 Module 3 Conclusion Locked
+ 04 MCP Clients 4 lectures
01 Building a basic MCP client Locked
02 Handling bidirectional communication Locked
03 Parsing and routing server messages Locked
04 Module 4 Conclusion Locked
+ 05 Advanced Features 4 lectures
01 Sampling callbacks Locked
02 Roots Locked
03 Exposing Resources from a server Locked
04 Module 5 Conclusion Locked
+ 06 Production & Debugging 5 lectures
01 Stateless HTTP server configuration for scalability Locked
02 Debugging message flows using raw JSON-RPC Locked
03 Common issues when moving from stdio to HTTP in production Locked
04 Security considerations Locked
05 Module 6 Conclusion Locked
Description

About this course.

This course focuses on Model Context Protocol and what it takes to deploy MCP servers in real production environments, where performance and scalability actually matter.

► Understand Model Context Protocol in depth
► Design scalable MCP server architectures
► Deploy and manage MCP in production settings
► Optimize for performance at enterprise scale

✔️ Lifetime access to all modules

If you're serious about putting LLMs into production, this is the technical foundation you need.

Scale your AI the right way. Start now.

Ready to start building?

Getting an LLM working is one thing. Getting it to work reliably at scale in production is a different challenge entirely.

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