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Course Outline

The Protocol Anatomy

  • Understanding why function calling alone is insufficient for complex agent ecosystems
  • Exploring MCP primitives: tools, resources, prompts, and their JSON schemas
  • Examining the lifecycle of an MCP session: initialize, list tools, call, return, and shutdown
  • Comparing MCP with OpenAPI and GraphQL for exposing capabilities to agents

Building a Stdio MCP Server

  • Scaffolding a TypeScript MCP server using the official SDK
  • Defining tool schemas with Zod and generating runtime validation
  • Implementing tool handlers that interact with internal REST APIs or databases
  • Managing errors, partial results, and long-running tool execution

Building an HTTP MCP Server

  • Transitioning from stdio to HTTP to enable remote deployment and load balancing
  • Implementing authentication via bearer tokens and mTLS
  • Handling graceful degradation when HTTP connections fail mid-session
  • Deploying HTTP MCP servers behind Kong or nginx with rate limiting capabilities

Client Integration Patterns

  • Registering an MCP server with Claude Code using the configuration file
  • Connecting OpenClaude to multiple MCP endpoints simultaneously
  • Developing a custom Python agent client using the MCP Python SDK
  • Gracefully managing changes in tool availability at runtime

Resource and Prompt Exposure

  • Exposing read-only resources to enrich agent context
  • Creating parameterized prompt templates to guide agent reasoning
  • Dynamically updating resources when underlying data changes
  • Separating mutable tools from immutable resources for enhanced security clarity

Internal Tool Registry and Discovery

  • Constructing a company-wide MCP registry with metadata and ownership tags
  • Facilitating auto-discovery via DNS-SD or well-known endpoint files
  • Versioning tools and deprecating old endpoints without disrupting clients
  • Cataloging tools with natural language descriptions to improve agent searchability

Enterprise Security Boundaries

  • Implementing authorization checks within tool handlers based on agent identity
  • Utilizing network segmentation to isolate high-risk tools from general agent access
  • Sandboxing tool execution using seccomp and gVisor containers
  • Logging every tool invocation for compliance and forensic analysis

Performance and Reliability Engineering

  • Establishing timeout policies per tool family: database, compute, and external APIs
  • Implementing circuit breakers when downstream services are unhealthy
  • Caching tool results to reduce redundant expensive computations
  • Running MCP servers as sidecars versus standalone microservices

Interoperability Across Agent Platforms

  • Testing MCP server compatibility with Claude Code and Continue.dev clients
  • Navigating transport negotiation differences between platforms
  • Writing polyfill adapters for non-MCP agent frameworks
  • Building a cross-platform tool marketplace within the organization

Evolving the MCP Ecosystem Internally

  • Gathering developer feedback on tool usefulness and accuracy
  • Conducting quarterly tool audits and pruning obsolete integrations
  • Onboarding new teams with self-service MCP server templates
  • Contributing improvements upstream to the open-source MCP specification

Requirements

  • Programming experience in TypeScript or Python
  • Familiarity with LLM tool calling and function-calling patterns
  • Basic networking knowledge, including HTTP, WebSockets, and JSON-RPC

Audience

  • Backend developers creating custom tools for AI agents
  • Platform engineers standardizing how AI agents access enterprise systems
  • Solution architects designing AI tool ecosystems for corporate adoption
 14 Hours

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Provisional Upcoming Courses (Require 5+ participants)

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