Polaris ML/AI Training

MCP Bootcamp: Build an AI-Powered Customer Support Agent

intermediate18h13 lessons

Master the Model Context Protocol by building a complete AI customer support system. In 13 hands-on lessons, you'll create MCP servers for ticketing, knowledge base search, CRM integration, and email — then orchestrate them into one intelligent support agent powered by Claude. Bilingual content (English + 中文).

MCPModel Context ProtocolClaudeTypeScriptAI AgentCustomer SupportMCP ServerToolsResourcesAnthropicZodJSON-RPC

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Lesson Overview

1

Lesson 1: What is MCP?

Understand the problem MCP solves, how the protocol works, and meet the TechFlow customer support scenario you will build throughout this bootcamp.

2

Lesson 2: Your First MCP Server

Install the MCP TypeScript SDK, build a greeting server with one tool, test it in MCP Inspector, and connect it to Claude Desktop.

3

Lesson 3: Tools Deep Dive

Master MCP tool anatomy, Zod schema patterns, return content types, error handling, async tools, and build a multi-tool utility server.

4

Lesson 4: Resources — Giving AI Context

Learn how MCP resources let AI models read structured data from your servers. Build a config resource server with URI templates and subscriptions, then test it in MCP Inspector.

5

Lesson 5: Prompts & Server Patterns

Master MCP prompt templates and learn how to structure a production-grade MCP server. Add reusable support_triage and kb_search prompts to the TechFlow utility server, and learn the stdio logging pitfall that silently corrupts JSON-RPC.

6

Lesson 6: Building the Ticket Management Server

Build a full MCP server that manages TechFlow support tickets. Implement five CRUD tools, two resources, and seed real data — then test end-to-end in MCP Inspector and Claude Desktop.

7

Lesson 7: Building the Knowledge Base Server

Build an MCP server that powers the TechFlow knowledge base — keyword search with TF-IDF-style relevance scoring, category hierarchy, article resources, and seeded data from articles.json.

8

Lesson 8: Customer CRM Server

Model TechFlow's customer data, understand customer-ticket relationships and PII privacy rules, then build a full MCP CRM server with tools and resources for customer lookup, history, and notes.

9

Lesson 9: Email & Notification Server

Learn safety-first design for AI-driven communications — confirmation flows, template-based messaging, and rate limiting — then build a complete MCP email server with human-in-the-loop sending and mock delivery.

10

Lesson 10: Multi-Server Orchestration

Run all four MCP servers simultaneously in Claude Desktop, configure multi-server routing, and execute end-to-end customer support workflows that span ticket, CRM, knowledge base, and email servers.

11

Lesson 11: HTTP Transport & Remote Deployment

Convert your MCP ticket server from stdio to Streamable HTTP transport, add API key authentication, deploy with Express, and compare the tradeoffs between local stdio and remote HTTP for production MCP servers.

12

Lesson 12: Production Patterns & Best Practices

Make your MCP servers production-ready with structured logging, unit testing, input sanitization, response caching, and health checks. Learn the patterns that separate hobby projects from systems that run reliably at scale.

13

Lesson 13: Capstone — Full Customer Support Agent

Bring everything together. Build the complete TechFlow customer support agent: a five-step workflow spanning all four MCP servers, a metrics dashboard server, and a full end-to-end test with five realistic support conversations.

MCP Bootcamp: Build an AI-Powered Customer Support Agent | ML/AI Bootcamp | Polaris ML/AI Training