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Course Outline

Anatomy of the Protocol

  • Limitations of function calling alone in complex agent ecosystems
  • Core MCP components: tools, resources, prompts, and their JSON schemas
  • MCP session lifecycle: initialization, tool listing, invocation, response, and termination
  • Comparison of MCP against OpenAPI and GraphQL for exposing capabilities to agents

Creating a Stdio MCP Server

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

Creating an HTTP MCP Server

  • Migrating from stdio to HTTP for remote deployment and load balancing
  • Implementing authentication via bearer tokens and mTLS
  • Handling graceful degradation during HTTP connection failures mid-session
  • Deploying HTTP MCP servers behind Kong or nginx with rate limiting

Client Integration Strategies

  • Registering MCP servers with Claude Code via configuration files
  • Linking OpenClaude to multiple MCP endpoints concurrently
  • Developing a custom Python agent client using the MCP Python SDK
  • Managing dynamic changes in tool availability at runtime

Resource and Prompt Exposure

  • Providing read-only resources to enrich agent context
  • Designing parameterized prompt templates to steer agent reasoning
  • Dynamically updating resources as underlying data shifts
  • Distinguishing between mutable tools and immutable resources for security clarity

Internal Tool Registry and Discovery

  • Constructing an organization-wide MCP registry with metadata and ownership labels
  • Enabling auto-discovery through DNS-SD or well-known endpoint files
  • Managing tool versions and retiring legacy endpoints without disrupting clients
  • Cataloging tools with natural language descriptions to enhance agent searchability

Enterprise Security Perimeters

  • Enforcing authorization checks within tool handlers based on agent identity
  • Isolating high-risk tools from general agent access via network segmentation
  • Sandboxing tool execution using seccomp and gVisor containers
  • Logging all tool invocations for compliance and forensic review

Performance and Reliability Engineering

  • Configuring timeout policies for tool categories: databases, compute, and external APIs
  • Implementing circuit breakers when downstream services exhibit instability
  • Caching tool results to minimize redundant, high-cost computations
  • Deploying MCP servers as sidecars versus standalone microservices

Cross-Platform Interoperability

  • Verifying MCP server compatibility with Claude Code and Continue.dev clients
  • Addressing transport negotiation variances across different platforms
  • Developing polyfill adapters for non-MCP agent frameworks
  • Establishing an internal cross-platform tool marketplace

Internal Evolution of the MCP Ecosystem

  • Gathering developer insights on tool utility and precision
  • Conducting quarterly tool audits to remove outdated integrations
  • Onboarding new teams using self-service MCP server templates
  • Contributing enhancements upstream to the open-source MCP specification

Requirements

  • Proficiency in TypeScript or Python development
  • Conceptual understanding of LLM tool calling and function-calling mechanisms
  • Fundamental networking knowledge, including HTTP, WebSockets, and JSON-RPC

Target Audience

  • Backend engineers creating bespoke tools for AI agents
  • Platform engineers standardizing AI agent access to enterprise systems
  • Solution architects planning AI tool ecosystems for corporate deployment
 14 Hours

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