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Course Outline
The Protocol Anatomy
- Why function calling alone is inadequate for complex agent ecosystems
- MCP primitives: tools, resources, prompts, and their JSON schemas
- The lifecycle of an MCP session: initialization, tool listing, invocation, result return, and shutdown
- Comparing MCP with OpenAPI and GraphQL for exposing capabilities to agents
Building a Stdio MCP Server
- Setting up a TypeScript MCP server using the official SDK
- Defining tool schemas with Zod and generating runtime validation
- Implementing tool handlers that interface 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 for remote deployment and load balancing
- Implementing authentication via bearer tokens and mTLS
- Graceful degradation when HTTP connections fail mid-session
- Deploying HTTP MCP servers behind Kong or nginx with rate limiting
Client Integration Patterns
- Registering an MCP server with Claude Code using the configuration file
- Linking 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 for agent context enrichment
- Creating parameterized prompt templates that guide agent reasoning
- Updating resources dynamically as underlying data changes
- Distinguishing mutable tools from immutable resources for security clarity
Internal Tool Registry and Discovery
- Constructing a company-wide MCP registry with metadata and ownership tags
- 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 for 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 with 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
- Handling transport negotiation differences between platforms
- Writing polyfill adapters for non-MCP agent frameworks
- Building a cross-platform tool marketplace inside the organization
Evolving the MCP Ecosystem Internally
- Collecting developer feedback on tool usefulness and accuracy
- Running 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 proficiency in TypeScript or Python
- Familiarity with LLM tool calling and function-calling patterns
- Foundational networking knowledge: HTTP, WebSockets, and JSON-RPC
Audience
- Backend developers crafting custom tools for AI agents
- Platform engineers streamlining how AI agents access enterprise systems
- Solution architects designing AI tool ecosystems for corporate adoption
14 Hours
