AI Agent Engineering with LangChain and MCP: Production Patterns

AI Agent Engineering with LangChain and MCP: Production Patterns

Struggling to build reliable AI agents that scale in the real world?

Core Promise
"AI Agent Engineering with LangChain and MCP: Production Patterns" shows you how to move beyond prototypes and deploy full-fledged, production-ready AI agents. You'll master the tools, architectures, and workflows that power resilient, maintainable systems using LangChain and the Messaging Contract Protocol (MCP).

Key Learnings & Benefits
Discover actionable patterns and hands-on guidance to:

• Architect Robust Agents: Grasp core abstractions-chains, agents, memory-and design workflows that handle complex tasks and multi-agent coordination (Chapter 3).

• Integrate LLMs & External Tools: Build and secure API adapters, implement prompt engineering, and manage rate limits for rock-solid integrations (Chapter 4).

• Implement RAG Pipelines: Ingest data, choose the right vector stores, and fuse context with LLMs for accurate, up-to-date retrieval-augmented responses (Chapter 5).

• Deploy & Scale: Containerize with Docker, orchestrate on Kubernetes or serverless infrastructure, and leverage spot instances and autoscaling to optimize costs (Chapters 6 & 10).

• Automate MLOps & CI/CD: Craft end-to-end pipelines with GitHub Actions or GitLab CI, enforce testing, version models and data, and manage infrastructure as code with Terraform and Helm (Chapter 7).

• Ensure Observability & Security: Define metrics, instrument with Prometheus and OpenTelemetry, set up Grafana dashboards, and implement secrets management, encryption, and bias auditing (Chapters 8 & 9).

Each chapter combines clear explanations, production-tested examples, and personal insights-such as real-world pitfalls and recovery strategies-so you can confidently build AI agents that delight users and withstand the demands of live environments.

Equip yourself with proven production patterns for AI agent engineering-get your copy of AI Agent Engineering with LangChain and MCP: Production Patterns today!