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Course Outline

Understanding the Protocol Structure

  • Why function calling alone falls short in complex agent environments
  • Core MCP elements: tools, resources, prompts, and their corresponding JSON schemas
  • The lifecycle of an MCP session: initialization, tool listing, invocation, result return, and shutdown
  • Evaluating MCP against OpenAPI and GraphQL for exposing capabilities to agents

Creating a Stdio MCP Server

  • Setting up a TypeScript MCP server using the official SDK
  • Defining tool schemas with Zod and generating runtime validation
  • Developing tool handlers that interact with internal REST APIs or databases
  • Managing errors, partial results, and long-duration tool executions

Creating an HTTP MCP Server

  • Transitioning from stdio to HTTP for remote deployment and load balancing
  • Implementing authentication via bearer tokens and mTLS
  • Ensuring graceful degradation if HTTP connections drop mid-session
  • Deploying HTTP MCP servers behind Kong or nginx with rate limiting enabled

Client Integration Strategies

  • Registering an MCP server with Claude Code via configuration files
  • Connecting OpenClaude to multiple MCP endpoints concurrently
  • Developing a custom Python agent client utilizing the MCP Python SDK
  • Managing runtime changes in tool availability seamlessly

Exposing Resources and Prompts

  • Providing read-only resources to enrich agent context
  • Designing parameterized prompt templates to direct agent reasoning
  • Dynamically updating resources in response to underlying data changes
  • Distinguishing mutable tools from immutable resources for clearer security

Internal Tool Registry and Discovery

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

Enterprise Security Boundaries

  • Executing authorization checks within tool handlers based on agent identity
  • Applying network segmentation to isolate high-risk tools from general access
  • Sandboxing tool execution using seccomp and gVisor containers
  • Recording all tool invocations for compliance and forensic analysis

Performance and Reliability Engineering

  • Configuring timeout policies for different tool categories: database, compute, and external APIs
  • Deploying circuit breakers when downstream services exhibit instability
  • Caching tool outcomes to minimize redundant, costly computations
  • Evaluating MCP server deployment as sidecars versus standalone microservices

Interoperability Across Agent Platforms

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

Evolution of the Internal MCP Ecosystem

  • Gathering developer feedback on tool utility and accuracy
  • Conducting quarterly tool audits and removing obsolete integrations
  • Facilitating onboarding for new teams with self-service MCP server templates
  • Contributing enhancements upstream to the open-source MCP specification

Requirements

  • Familiarity with TypeScript or Python programming
  • Knowledge of LLM tool calling and function-calling mechanisms
  • Foundational understanding of networking protocols: HTTP, WebSockets, and JSON-RPC

Target Audience

  • Backend developers creating 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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