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Course Outline

The Protocol Anatomy

  • Why function calling alone is insufficient for complex agent ecosystems
  • MCP primitives: tools, resources, prompts, and their JSON schemas
  • Lifecycle of an MCP session: initialize, list tools, call, return, shutdown
  • Comparing MCP to OpenAPI and GraphQL for exposing capabilities to agents

Building a Stdio MCP Server

  • Scaffolding a TypeScript MCP server with the official SDK
  • Defining tool schemas with Zod and generating runtime validation
  • Implementing tool handlers that call internal REST APIs or databases
  • Handling errors, partial results, and long-running tool execution

Building an HTTP MCP Server

  • Upgrading from stdio to HTTP for remote deployment and load balancing
  • Implementing authentication using 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
  • Connecting OpenClaude to multiple MCP endpoints simultaneously
  • Writing a custom Python agent client using the MCP Python SDK
  • Gracefully handling tool availability changes 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 when underlying data changes
  • Separating mutable tools from immutable resources for security clarity

Internal Tool Registry and Discovery

  • Building 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 breaking clients
  • Cataloging tools with natural language descriptions for agent searchability

Enterprise Security Boundaries

  • Implementing authorization checks inside 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 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 experience in TypeScript or Python
  • Understanding of LLM tool calling and function-calling patterns
  • Basic networking knowledge: HTTP, WebSockets, and JSON-RPC

Audience

  • Backend developers building custom tools for AI agents
  • Platform engineers standardizing how AI agents access enterprise systems
  • Solution architects designing AI tool ecosystems for corporate adoption
 14 Hours

Custom Corporate Training

Training solutions designed exclusively for businesses.

  • Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
  • Flexible Schedule: Dates and times adapted to your team's agenda.
  • Format: Online (live), In-company (at your offices), or Hybrid.
Investment

Price per private group, online live training, starting from 2900 € + VAT*

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