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Course Outline

Protocol Anatomy

  • Why function calling alone falls short for complex agent ecosystems
  • MCP primitives: tools, resources, prompts, and their associated JSON schemas
  • MCP session lifecycle: initialization, listing tools, invocation, response, 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 invoke internal REST APIs or databases
  • Managing errors, partial results, and long-running tool executions

Building an HTTP MCP Server

  • Transitioning from stdio to HTTP for remote deployment and load balancing
  • Implementing authentication via bearer tokens and mTLS
  • Managing graceful degradation when HTTP connections drop during a session
  • Deploying HTTP MCP servers behind Kong or nginx with rate limiting

Client Integration Patterns

  • Registering an MCP server with Claude Code via the configuration file
  • Connecting OpenClaude to multiple MCP endpoints simultaneously
  • Developing a custom Python agent client using the MCP Python SDK
  • Handling changes in tool availability gracefully 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
  • Distinguishing between mutable tools and immutable resources for security clarity

Internal Tool Registry and Discovery

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

Enterprise Security Boundaries

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

Performance and Reliability Engineering

  • Setting timeout policies per tool category: database, compute, and external APIs
  • Implementing circuit breakers for unhealthy downstream services
  • Caching tool results to minimize 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
  • Addressing 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

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

Requirements

  • Proficiency in programming with TypeScript or Python
  • Familiarity with LLM tool calling and function-calling patterns
  • Foundational networking knowledge: HTTP, WebSockets, and JSON-RPC

Target Audience

  • Backend developers crafting custom tools for AI agents
  • Platform engineers standardizing AI agent access to enterprise systems
  • Solution architects designing AI tool ecosystems for corporate implementation
 14 Hours

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