Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Protocol Architecture Overview
- Evaluating limitations of function-only approaches in complex agent ecosystems
- Core Model Context Protocol (MCP) components: tools, resources, prompts, and associated JSON schemas
- MCP session lifecycle management: initialization, tool enumeration, execution, response handling, and termination
- Comparative analysis of MCP versus OpenAPI and GraphQL for exposing capabilities to agent systems
Implementation of a Standard Input/Output MCP Server
- Scaffolding a TypeScript-based MCP server using the official SDK
- Defining tool schemas with Zod to ensure runtime validation and integrity
- Developing tool handlers that interface with internal REST APIs or database systems
- Managing errors, partial results, and long-running execution processes
Implementation of an HTTP-based MCP Server
- Migrating from standard I/O to HTTP protocols to support remote deployment and load balancing
- Implementing authentication mechanisms using bearer tokens and mutual TLS (mTLS)
- Ensuring service continuity and graceful degradation during connection interruptions
- Deploying HTTP MCP servers behind reverse proxies such as Kong or nginx with integrated rate limiting
Client Integration Methodologies
- Registering MCP servers with Claude Code via configuration files
- Enabling concurrent connections to multiple MCP endpoints using OpenClaude
- Developing custom Python agent clients utilizing the MCP Python SDK
- Managing dynamic changes in tool availability during runtime operations
Resource and Prompt Management
- Exposing read-only resources to enhance agent context and situational awareness
- Creating parameterized prompt templates to standardize and guide agent reasoning processes
- Updating resource data dynamically in response to underlying source changes
- Distinguishing between mutable tools and immutable resources to clarify security boundaries
Internal Tool Registry and Discovery Infrastructure
- Establishing an enterprise-wide MCP registry with metadata tagging and ownership attribution
- Facilitating automatic discovery through DNS Service Discovery (DNS-SD) or well-known endpoint files
- Managing tool versioning and deprecation strategies to maintain client compatibility
- Documenting tools with natural language descriptions to improve agent searchability and discoverability
Enterprise Security Frameworks
- Enforcing authorization controls within tool handlers based on verified agent identity
- Utilizing network segmentation to isolate high-risk tools from standard agent access vectors
- Sandboxing tool execution environments using seccomp and gVisor container technologies
- Maintaining comprehensive logs of all tool invocations for compliance auditing and forensic analysis
Performance Optimization and Reliability Engineering
- Defining timeout policies tailored to specific tool categories, including database and external API interactions
- Implementing circuit breaker patterns to prevent cascading failures during downstream service disruptions
- Leveraging result caching to minimize redundant computational overhead
- Evaluating architectural deployments of MCP servers as sidecars versus standalone microservices
Cross-Platform Interoperability Standards
- Verifying MCP server compatibility across diverse client platforms, including Claude Code and Continue.dev
- Addressing transport negotiation discrepancies inherent to different agent frameworks
- Developing polyfill adapters to bridge non-MCP agent ecosystems with MCP standards
- Constructing an internal cross-platform tool marketplace to streamline organizational resource sharing
Ecosystem Evolution and Governance
- Gathering developer feedback to assess the utility and accuracy of integrated tools for government and public sector applications where relevant
- Conducting quarterly audits to prune obsolete integrations and maintain system efficiency
- Facilitating team onboarding through self-service MCP server templates
- Contributing technical improvements upstream to support the open-source MCP specification and broader industry standards
Requirements
- Proficiency in software development using TypeScript or Python.
- Familiarity with large language model (LLM) integration patterns, specifically regarding tool invocation and function-calling protocols.
- Foundational understanding of network communication standards, including HTTP, WebSockets, and JSON-RPC.
**Target Audience**
- Backend engineering professionals developing custom integrations for AI-driven workflows.
- Platform engineering staff establishing standardized methods for AI agents to interact with enterprise infrastructure.
- Solution architects responsible for designing scalable AI tool ecosystems to support organizational adoption.
This training curriculum is designed for government practitioners seeking to enhance technical capabilities in AI system integration and enterprise deployment strategies.
14 Hours
