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Course Outline

Protocol Structure

  • The limitations of function calling in complex agent ecosystems
  • Core MCP components: tools, resources, prompts, and their associated JSON schemas
  • The MCP session lifecycle: initialization, tool listing, invocation, response, and termination
  • A comparative analysis of MCP versus OpenAPI and GraphQL for agent capability exposure

Developing a Stdio MCP Server

  • Setting up a TypeScript MCP server using the official SDK
  • Defining tool schemas with Zod and establishing runtime validation
  • Creating tool handlers that interface with internal REST APIs or databases
  • Managing errors, partial outputs, and long-running execution tasks

Developing an HTTP MCP Server

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

Client Integration Strategies

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

Exposing Resources and Prompts

  • Providing read-only resources to enhance agent context
  • Designing parameterized prompt templates to direct agent reasoning
  • Dynamic resource updates in response to underlying data changes
  • Distinction between mutable tools and immutable resources for security clarity

Internal Registry and Discovery

  • Constructing a company-wide MCP registry with metadata and ownership tracking
  • Automated discovery through DNS-SD or well-known endpoint files
  • Tool versioning and safe deprecation of endpoints to prevent client disruption
  • Cataloging tools with natural language descriptions to improve agent searchability

Enterprise Security Frameworks

  • Enforcing 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
  • Comprehensive logging of tool invocations for compliance and forensic review

Performance and Reliability Engineering

  • Defining timeout policies for different tool categories: database, compute, and external APIs
  • Integrating circuit breakers for unstable downstream services
  • Optimizing performance by caching tool results to avoid redundant calculations
  • Evaluating MCP servers as sidecars versus standalone microservices

Cross-Platform Interoperability

  • Verifying MCP server compatibility with clients like Claude Code and Continue.dev
  • Addressing transport negotiation variances across different platforms
  • Creating polyfill adapters for agent frameworks not natively supporting MCP
  • Establishing an internal cross-platform tool marketplace

Internal Ecosystem Evolution

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

Requirements

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

Target Audience

  • Backend developers creating bespoke tools for AI agents
  • Platform engineers standardizing AI agent access to enterprise systems
  • Solution architects architecting AI tool ecosystems for broader corporate implementation
 14 Hours

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