Mastering MCP: Secure AI Orchestration & RAG with JSON‑RPC

All‑in‑one MCP training & practice exam: master JSON‑RPC, secure transports, RAG, multi‑agent workflows, and plug‑in ext

What you'll learn
- Master MCP core primitives: Tools, Resources, Prompts
- Implement JSON‑RPC for AI model integration
- Build and deploy MCP Clients & Servers
- Design schema‑validated RPC handlers
- Configure secure mTLS & token auth for MCP
- Apply retry, backoff, and circuit‑breaker patterns
- Integrate LLMs with external tools via MCP
- Develop Retrieval‑Augmented Generation (RAG) pipelines
- Orchestrate multi‑agent workflows with MCP
- Persist and retrieve context across sessions
- Monitor MCP deployments with metrics/logs
- Scale MCP servers using autoscaling policies
- Extend MCP via custom plug‑ins & middleware
- Troubleshoot and test MCP using contract tests
- Complete a capstone: end‑to‑end MCP application

Requirements
- Basic familiarity with HTTP and JSON formats
- Understanding of RESTful API concepts
- No prior MCP or advanced AI experience needed
- A modern code editor and terminal access
- (Optional) Access to a local Kubernetes or Docker

Description
This comprehensive Model Context Protocol (MCP) course plus integrated practice–exam bundle is your definitive path to becoming a high‑level expert in modern AI orchestration. Whether you are an AI engineer, backend developer, DevOps professional, or technical architect, this program equips you with everything—from core primitives to advanced multi‑agent workflows—so you can design, build, secure, deploy, and scale production‑grade MCP systems. You will not only learn by doing through hands‑on labs and real‑world use‑cases but also validate your mastery via robust practice tests modeled on MCP certification standards. If you want the most thorough, practical, and forward‑thinking MCP training available, this is the course you’ve been waiting for.

Why This Course Stands Above the Rest

Dual Structure: Learning + Practice ExamThis isn’t just a lecture series—it’s an end‑to‑end training and self‑assessment platform. Each technical module is paired with a practice test section, emulating the rigor and format of professional MCP certification exams. You learn concepts, apply them in hands‑on workshops, then immediately reinforce and validate your understanding through challenging quizzes and realistic scenario‑based questions.

Unparalleled Breadth & DepthWe begin with the fundamentals—JSON‑RPC request/response structures, core MCP primitives (Tools, Resources, Prompts, Streams, Agents), and best practices for schema validation and idempotency. From there, we go deep: advanced orchestration patterns, authentication and authorization models, transport layer security (mTLS and JWT), observability and monitoring, performance tuning, multi‑agent pipelines, RAG integrations, and custom plug‑in ecosystems. By the time you finish, you will have encyclopedic command of MCP design, development, and operations.

Hands‑On, Workshop‑Driven LearningPassive listening is not enough. You’ll spin up real embed servers, vector search resources, LLM prompt layers, and multi‑service pipelines via Docker Compose and Kubernetes. You’ll build a Retrieval‑Augmented Generation chatbot, orchestrate multi‑agent task planners, and implement a secure, audited data ingestion service. Each workshop comes with step‑by‑step guidance, from environment setup through production deployment, so you graduate with tangible, deployable MCP applications in your portfolio.

Certification‑Style Practice TestsOver 200+ meticulously crafted multiple‑choice questions span every section. Each quiz question includes four professional distractors, one correct answer, and a concise explanation. You’ll encounter questions on JSON‑RPC error codes, schema constraints, authentication flows, metrics queries, autoscaling triggers, plug‑in manifests, and security hardening. These practice tests mirror the difficulty and pacing of MCP certification exams, ensuring you go into any real assessment with confidence.

Production‑Ready Best PracticesBeyond code, you learn the “why.” Topics include zero‑downtime deployment strategies like blue/green and canary rollouts; GitOps for CI/CD pipelines; contract testing with Pact; chaos‑engineering resilience checks; defense‑in‑depth security models; audit logging and compliance; and post‑release observability with Prometheus and Grafana. Every pattern and recommendation is battle‑tested in real enterprises, so you can deploy MCP solutions that survive scale, threat, and compliance demands.

Who Should Enroll

AI‑First Developers & EngineersIf you’re integrating large‑language models into complex toolchains, building AI‑powered applications, or automating workflows, MCP is your unifying standard—and this course shows you exactly how to harness it.

Backend & Platform SpecialistsMCP bridges microservices, external APIs, and AI. Learn to design RPC‑based services, secure them at scale, and connect them seamlessly to vector databases, LLM endpoints, and orchestration controllers.

DevOps/Cloud PractitionersWith Kubernetes, Docker, CI/CD, and observability modules built in, this course teaches you to deploy, monitor, autoscale, and troubleshoot MCP stacks in production environments.

Technical Architects & ConsultantsGain the conceptual and practical foundation to lead MCP adoption at your organization—draft specifications, run proof‑of‑concepts, guide plugin ecosystems, and establish governance around schema evolution.

Certification AspirantsIf you’re preparing for MCP Practitioner or related credentials, this course’s curated practice exams, in‑depth article readings, and capstone demos give you the targeted preparation you need to excel.

What You’ll Build and Master

MCP Primitives & RPC Fundamentals• JSON‑RPC schema enforcement and idempotency patterns• Tools for side‑effects, Resources for data retrieval, Prompts for LLM orchestration, Streams for real‑time events, Agents for coordination

Advanced Orchestration & Context Persistence• Prompt engineering, dynamic templates, fallback strategies• JWT scopes, OAuth2, mTLS mutual authentication• Episodic vs. semantic memory stores, sharding, eviction policies• Circuit breakers, exponential backoff, and retry budgets

Transport Design & Observability• HTTP best practices: POST endpoints, CORS, chunked transfer, HTTP/2 multiplexing• Structured logging, distributed tracing, Prometheus metrics, Grafana dashboards, alerting workflows• Performance tuning: caching, batching, concurrency models, HPA on custom metrics

Client & Server Lifecycle Patterns• Client discovery, schema caching, version negotiation, heartbeat health checks• Server bootstrapping, handler registration, middleware chaining (auth → validation → logging → metrics → business)• Graceful shutdown, zero‑downtime deployments, plugin frameworks, hot‑reload, sandbox isolation

Secure AI Workflows & RAG Pipelines• End‑to‑end Retrieval‑Augmented Generation chatbot with embedding, vector search, streaming prompts• Multi‑agent planning, dispatch, status streaming, aggregation with autoscaling• Secure data ingestion services with mTLS, scoped tokens, idempotent writes, audit‑hardened logs

Plugin Ecosystem & Extensibility• Writing plugin manifests, version compatibility, dependency isolation, conflict resolution• Client‑side middleware hooks, transport adapters, plugin sandboxing• Server‑side extensions, custom metrics collectors, rate‑limit & A/B testing middleware

Testing, CI/CD & Deployment Patterns• Unit, contract (Pact), integration, and end‑to‑end tests in CI pipelines• Schema validation gates, automated vulnerability scanning, code coverage dashboards• Blue/green, canary, and automated rollback strategies in GitOps workflows

Security Hardening & Token Lifecycle• TLS/mTLS configuration, cipher suite enforcement, certificate rotation, pinning• OAuth2 flows, JWT structure, claims validation, introspection• Token revocation, refresh rotation, signing key management, zero‑trust hybrid models

Capstone Projects & Real‑World Demos• AI customer‑support chatbot with sub‑200 ms p95 latency• Multi‑agent automation pipeline with streaming dashboards and resilience tests• Secure data‑processing service with tamper‑evident audit logs and compliance checks• Final capstone presentation skills and community contribution guidelines

Course Format & Resources

35+ Video Lectures:Deep-dive narrative segments, demo-driven explanations, no code‑only monologues

2+ Hands‑On Workshops:Step‑by‑step lab guides with Docker Compose and Kubernetes manifests

200+ Practice MCQs:Section‑level quizzes and two full practice exams with detailed answer rationales

Why MCP Expertise Matters

The AI landscape is rapidly evolving. Modern applications demand secure, standardized, and scalable communication between LLMs, external services, and orchestrated agents. MCP is emerging as the industry‑leading convention to solve this challenge. By mastering MCP, you position yourself at the forefront of AI infrastructure design, able to integrate cutting‑edge models with enterprise systems, handle rapid scale, and meet stringent security and compliance demands. MCP proficiency unlocks roles in AI engineering, platform architecture, and DevOps leadership—making you a highly sought‑after talent in a competitive market.

Enroll nowto transform from curious technologist to MCP Maestro. Build real MCP systems, pass practice exams with flying colors, and claim your seat among the elite architects of next‑generation AI orchestration.

Your journey to MCP mastery—and unparalleled career growth—starts here.

Who this course is for:
- AI engineers integrating LLMs with external tools
- Backend developers building RPC‑based services
- DevOps/Platform engineers deploying MCP clusters
- Architects designing multi-agent AI systems
- Technical leads standardizing AI‑service interfaces
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