Building Production-Ready MCP Servers and Clients for Enterprise Teams Training Course
This practical course on constructing production-ready MCP servers and clients for enterprise teams focuses on the design, deployment, and operational management of Model Context Protocol solutions tailored for real-world business applications.
Delivered as an instructor-led live training (available online or onsite), this programme is designed for intermediate developers, architects, and platform engineers aiming to leverage MCP to develop reliable servers and clients that adhere to corporate standards regarding security, observability, versioning, and operational readiness.
Upon completion of this training, participants will be equipped to:
- Articulate the functionality of MCP servers and clients within an enterprise context.
- Develop MCP components characterised by well-defined contracts, rigorous validation, and robust error handling.
- Deploy and monitor MCP services incorporating logging, metrics, retry mechanisms, and health checks.
- Implement practical patterns for versioning, testing, security, and ongoing production support.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical practice.
- Hands-on implementation within a live laboratory environment.
Customisation Options
- To arrange a bespoke training session for this course, please contact us.
Course Outline
MCP Foundations and Enterprise Use Cases
- Understanding the Model Context Protocol and its role in corporate AI integration.
- Exploring how MCP servers and clients interact with models, tools, and backend systems.
- Examining common use cases, benefits, and constraints within team-based environments.
- Identifying key design considerations for production adoption.
Designing MCP Servers and Clients
- Defining capabilities, contracts, and clear responsibilities between server and client components.
- Structuring tools, resources, and prompts for maintainability and reuse.
- Applying validation, consistent outputs, and informative error responses.
- Designing workflows suitable for team ownership and support.
Reliability and Security in Production
- Addressing failures, invalid requests, and downstream service issues.
- Utilising timeouts, retries, fallback strategies, and safe processing patterns.
- Implementing fundamentals of authentication, authorisation, and secret handling.
- Ensuring auditability and controlled access to corporate tools and data.
Deployment, Observability, and Operations
- Packaging and deploying MCP services in local, containerised, or cloud environments.
- Managing configuration, environmental differences, and release workflows.
- Implementing logs, metrics, health checks, and alerting for runtime visibility.
- Troubleshooting common operational issues across clients and backend integrations.
Testing, Versioning, and Change Management
- Developing unit, integration, and contract tests for MCP workflows.
- Managing interface changes and compatibility over time.
- Validating releases prior to rollout and mitigating upgrade risks.
- Using practical readiness checks for ongoing support and maintenance.
Hands-On Implementation Workshop
- Constructing a simple enterprise-ready MCP server and client workflow.
- Applying validation, resilience, security, and observability practices.
- Reviewing a production readiness checklist.
- Planning next steps for adoption within internal teams and platforms.
Requirements
- Familiarity with APIs, JSON, and fundamental client-server integration concepts.
- Experience utilising command-line tools, Git, and basic application deployment workflows.
- Foundational programming experience in Python, JavaScript, or a comparable language.
Target Audience
- Software developers creating MCP-enabled applications and integrations.
- Solution architects and technical leads tasked with corporate AI integration.
- Platform, DevOps, and engineering teams responsible for supporting production MCP services.
Need help picking the right course?
southafrica@nobleprog.co.za or +27 (0)10 005 5793
Building Production-Ready MCP Servers and Clients for Enterprise Teams Training Course - Enquiry
Related Courses
Advanced LangGraph: Optimization, Debugging, and Monitoring Complex Graphs
35 HoursLangGraph is a framework designed for constructing stateful, multi-agent LLM applications as composable graphs, featuring persistent state and precise control over execution flow.
This instructor-led, live training (available online or onsite) targets advanced-level AI platform engineers, AI DevOps specialists, and ML architects who wish to optimize, debug, monitor, and manage production-grade LangGraph systems.
Upon completion of this training, participants will be able to:
- Design and optimize complex LangGraph topologies for speed, cost-efficiency, and scalability.
- Enhance reliability through retries, timeouts, idempotency, and checkpoint-based recovery.
- Debug and trace graph executions, inspect state, and systematically reproduce production issues.
- Instrument graphs with logs, metrics, and traces; deploy to production; and monitor SLAs and costs.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Building Coding Agents with Devstral: From Agent Design to Tooling
14 HoursDevstral is an open-source framework engineered for the creation and execution of coding agents capable of interacting with codebases, developer utilities, and APIs to boost engineering productivity.
This instructor-led, live training session (available online or onsite) targets intermediate to advanced ML engineers, developer-tooling teams, and SREs aiming to design, implement, and optimise coding agents using Devstral.
Upon completion of this training, participants will be able to:
- Set up and configure Devstral for coding agent development.
- Design agentic workflows for codebase exploration and modification.
- Integrate coding agents with developer tools and APIs.
- Implement best practices for secure and efficient agent deployment.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical sessions.
- Hands-on implementation within a live-lab environment.
Course Customisation Options
- To request a tailored training for this course, please contact us to arrange.
Open-Source Model Ops: Self-Hosting, Fine-Tuning and Governance with Devstral & Mistral Models
14 HoursDevstral and Mistral models are open-source AI technologies crafted for flexible deployment, fine-tuning, and scalable integration.
This instructor-led, live training (available online or onsite) targets intermediate to advanced ML engineers, platform teams, and research engineers keen on self-hosting, fine-tuning, and governing Mistral and Devstral models within production environments.
Upon completion of this training, participants will be able to:
- Set up and configure self-hosted environments for Mistral and Devstral models.
- Apply fine-tuning techniques to enhance domain-specific performance.
- Implement versioning, monitoring, and lifecycle governance protocols.
- Ensure security, compliance, and responsible usage of open-source models.
Course Format
- Interactive lectures and discussions.
- Hands-on exercises focused on self-hosting and fine-tuning.
- Live-lab implementation of governance and monitoring pipelines.
Course Customization Options
- To request a customized training session for this course, please contact us to arrange details.
LangGraph Applications in Finance
35 HoursLangGraph serves as a framework for constructing stateful, multi-actor LLM applications through composable graphs, featuring persistent state and precise control over execution processes.
This instructor-led, live training—available both online and onsite—is designed for intermediate to advanced professionals aiming to design, implement, and manage LangGraph-based finance solutions with appropriate governance, observability, and compliance standards.
Upon completion of this training, participants will be capable of:
- Designing finance-specific LangGraph workflows that align with regulatory and audit requirements.
- Integrating financial data standards and ontologies into graph state and tooling.
- Implementing reliability, safety, and human-in-the-loop controls for critical processes.
- Deploying, monitoring, and optimizing LangGraph systems to meet performance, cost, and SLA targets.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical sessions.
- Hands-on implementation within a live-lab environment.
Customization Options
- To arrange customized training for this course, please contact us directly.
LangGraph Foundations: Graph-Based LLM Prompting and Chaining
14 HoursLangGraph is a framework designed for constructing LLM applications structured around graphs, enabling capabilities such as planning, branching, tool utilisation, memory management, and controlled execution.
This instructor-led, live training (available online or on-site) targets beginner-level developers, prompt engineers, and data practitioners who aim to design and construct reliable, multi-step LLM workflows using LangGraph.
Upon completion of this training, participants will be able to:
- Articulate core LangGraph concepts (nodes, edges, state) and understand when to apply them.
- Construct prompt chains that branch, invoke tools, and retain memory.
- Integrate retrieval mechanisms and external APIs into graph workflows.
- Test, debug, and evaluate LangGraph applications for reliability and safety.
Course Format
- Interactive lectures and facilitated discussions.
- Guided labs and code walkthroughs within a sandbox environment.
- Scenario-based exercises focusing on design, testing, and evaluation.
Customization Options
- To request custom training for this course, please contact us to arrange.
LangGraph in Healthcare: Workflow Orchestration for Regulated Environments
35 HoursLangGraph facilitates stateful, multi-actor workflows driven by LLMs, offering precise control over execution paths and state persistence. In the healthcare sector, these capabilities are essential for ensuring compliance, achieving interoperability, and developing decision-support systems that align with clinical workflows.
This instructor-led training, available online or onsite, is designed for intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based healthcare solutions while navigating regulatory, ethical, and operational challenges.
Upon completing this training, participants will be able to:
- Design healthcare-specific LangGraph workflows that prioritise compliance and auditability.
- Integrate LangGraph applications with medical ontologies and standards such as FHIR, SNOMED CT, and ICD.
- Apply best practices for reliability, traceability, and explainability in sensitive environments.
- Deploy, monitor, and validate LangGraph applications within healthcare production settings.
Format of the Course
- Interactive lectures and discussions.
- Hands-on exercises using real-world case studies.
- Implementation practice in a live laboratory environment.
Course Customization Options
- To request customized training for this course, please contact us to arrange.
LangGraph for Legal Applications
35 HoursLangGraph serves as a framework for developing stateful, multi-actor LLM applications through composable graphs that feature persistent state and precise execution control.
This instructor-led, live training, available online or onsite, targets intermediate to advanced professionals seeking to design, implement, and operate LangGraph-based legal solutions equipped with the necessary compliance, traceability, and governance controls.
Upon completion of this training, participants will be capable of:
- Designing legal-specific LangGraph workflows that maintain auditability and compliance.
- Integrating legal ontologies and document standards into graph state and processing.
- Implementing guardrails, human-in-the-loop approvals, and traceable decision paths.
- Deploying, monitoring, and maintaining LangGraph services in production environments with observability and cost controls.
Course Format
- Interactive lectures and discussions.
- Numerous exercises and practice sessions.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request customized training for this course, please contact us to arrange.
Building Dynamic Workflows with LangGraph and LLM Agents
14 HoursLangGraph serves as a framework designed for composing graph-structured workflows involving Large Language Models (LLMs). It supports features such as branching, tool utilization, memory management, and controllable execution.
This instructor-led, live training session (available online or on-site) is tailored for intermediate-level engineers and product teams. The objective is to combine LangGraph’s graph logic with LLM agent loops to create dynamic, context-aware applications, including customer support agents, decision trees, and information retrieval systems.
Upon completion of this training, participants will be equipped to:
- Design graph-based workflows that effectively coordinate LLM agents, tools, and memory.
- Implement conditional routing, retry mechanisms, and fallback strategies to ensure robust execution.
- Integrate retrieval processes, APIs, and structured outputs into agent loops.
- Evaluate, monitor, and enhance agent behaviour to ensure reliability and safety.
Course Format
- Interactive lectures and facilitated discussions.
- Guided laboratory sessions and code walkthroughs within a sandbox environment.
- Scenario-based design exercises and peer reviews.
Course Customization Options
- To request customized training for this course, please contact us to arrange.
LangGraph for Marketing Automation
14 HoursLangGraph is a graph-based orchestration framework that enables conditional, multi-step LLM and tool workflows, ideal for automating and personalizing content pipelines.
This instructor-led, live training (online or onsite) is aimed at intermediate-level marketers, content strategists, and automation developers who wish to implement dynamic, branching email campaigns and content generation pipelines using LangGraph.
By the end of this training, participants will be able to:
- Design graph-structured content and email workflows with conditional logic.
- Integrate LLMs, APIs, and data sources for automated personalization.
- Manage state, memory, and context across multi-step campaigns.
- Evaluate, monitor, and optimize workflow performance and delivery outcomes.
Format of the Course
- Interactive lectures and group discussions.
- Hands-on labs implementing email workflows and content pipelines.
- Scenario-based exercises on personalization, segmentation, and branching logic.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Le Chat Enterprise: Private ChatOps, Integrations & Admin Controls
14 HoursLe Chat Enterprise offers a private ChatOps solution that delivers secure, adaptable, and governed conversational AI capabilities for organisations, supporting RBAC, SSO, connectors, and enterprise app integrations.
This instructor-led, live training (available online or onsite) targets intermediate-level product managers, IT leads, solution engineers, and security/compliance teams who wish to deploy, configure, and govern Le Chat Enterprise in enterprise environments.
By the end of this training, participants will be able to:
- Set up and configure Le Chat Enterprise for secure deployments.
- Enable RBAC, SSO, and compliance-driven controls.
- Integrate Le Chat with enterprise applications and data stores.
- Design and implement governance and admin playbooks for ChatOps.
Format of the Course
- Interactive lecture and discussion.
- Ample exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Cost-Effective LLM Architectures: Mistral at Scale (Performance / Cost Engineering)
14 HoursMistral represents a high-performance family of large language models, specifically optimised for cost-efficient production deployment at scale.
This instructor-led, live training (available online or onsite) is targeted at senior infrastructure engineers, cloud architects, and MLOps leads who seek to design, deploy, and optimise Mistral-based architectures to achieve maximum throughput with minimal cost.
Upon completing this training, participants will be able to:
- Implement scalable deployment patterns for Mistral Medium 3.
- Apply batching, quantization, and efficient serving strategies.
- Optimize inference costs while maintaining performance.
- Design production-ready serving topologies for enterprise workloads.
Format of the Course
- Interactive lecture and discussion.
- Extensive exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Productizing Conversational Assistants with Mistral Connectors & Integrations
14 HoursMistral AI is an open-source artificial intelligence platform that empowers teams to develop and embed conversational assistants into enterprise and customer-facing workflows.
This instructor-led live training, available online or onsite, is tailored for beginner to intermediate product managers, full-stack developers, and integration engineers who aim to design, integrate, and productise conversational assistants using Mistral connectors and integrations.
Upon completion of this training, participants will be equipped to:
- Integrate Mistral conversational models with enterprise and SaaS connectors.
- Implement retrieval-augmented generation (RAG) to ensure grounded responses.
- Design user experience patterns for both internal and external chat assistants.
- Deploy assistants into product workflows to address real-world use cases.
Format of the Course
- Interactive lectures and discussions.
- Hands-on integration exercises.
- Live laboratory development of conversational assistants.
Course Customization Options
- To request customized training for this course, please contact us to make arrangements.
Enterprise-Grade Deployments with Mistral Medium 3
14 HoursMistral Medium 3 is a high-performance, multimodal large language model designed for production-grade deployment across enterprise environments.
This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level AI/ML engineers, platform architects, and MLOps teams who wish to deploy, optimize, and secure Mistral Medium 3 for enterprise use cases.
By the end of this training, participants will be able to:
- Deploy Mistral Medium 3 using API and self-hosted options.
- Optimize inference performance and costs.
- Implement multimodal use cases with Mistral Medium 3.
- Apply security and compliance best practices for enterprise environments.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Mistral for Responsible AI: Privacy, Data Residency & Enterprise Controls
14 HoursMistral AI offers an open-source, enterprise-ready AI platform equipped with features designed to facilitate secure, compliant, and responsible AI deployment.
This instructor-led training, available either online or onsite, targets intermediate-level compliance leads, security architects, and legal/operations stakeholders seeking to implement responsible AI practices via Mistral, specifically by leveraging privacy safeguards, data residency options, and enterprise control mechanisms.
Upon completion of this training, participants will be able to:
- Implement privacy-preserving techniques within Mistral deployments.
- Apply data residency strategies to ensure regulatory compliance.
- Establish enterprise-grade controls, including RBAC, SSO, and audit logs.
- Evaluate vendor and deployment options to align with compliance standards.
Format of the Course
- Interactive lectures and discussions.
- Case studies and exercises focused on compliance.
- Practical implementation of enterprise AI controls.
Course Customization Options
- To request customized training for this course, please contact us to make arrangements.
Multimodal Applications with Mistral Models (Vision, OCR, & Document Understanding)
14 HoursMistral models are open-source AI technologies that have expanded into multimodal workflows, supporting both language processing and visual tasks for enterprise and research purposes.
This instructor-led, live training (available online or on-site) is designed for intermediate-level ML researchers, applied engineers, and product teams who aim to create multimodal applications using Mistral models, including OCR and document analysis pipelines.
Upon completing this training, participants will be able to:
- Set up and configure Mistral models for multimodal tasks.
- Implement OCR workflows and integrate them with NLP pipelines.
- Design document analysis applications for enterprise use cases.
- Develop vision-text search and assistive UI functionalities.
Course Format
- Interactive lectures and discussions.
- Practical coding exercises.
- Live laboratory implementation of multimodal pipelines.
Customization Options
- To request a customized training for this course, please contact us to arrange.