Step-by-step tutorial: Build your first MCP server from absolute zero. Learn the MCP protocol architecture, server lifecycle, project setup with Node.js/TypeScript, your first tool, and testing with MCP Inspector.

The final post in the Agent Security series: how to assemble everything into a production defense stack. Defense in depth for AI agents, security architecture patterns, incident response for agent breaches, monitoring and alerting, and a complete production-ready security configuration.

How to audit AI agents for compliance frameworks. Audit trails, conversation logging, explainability, data retention, PII handling, SOC2 controls for agents, GDPR right to explanation, and PCI compliance for agent payment processing.

How to secure MCP servers in production. Transport security (stdio vs SSE vs WebSocket), OAuth authentication flows, API key management, request validation, rate limiting, and production deployment patterns for MCP.

How to secure tool access for AI agents in production. Least privilege principles, MCP server scoping, tool call validation, parameter whitelisting, credential management, and production patterns for securing agent tool access.

A deep dive into prompt injection attacks against AI agents in 2026. Direct injection, indirect injection, jailbreaking, and the defense patterns that actually work in production — input guardrails, output validation, tool sandboxing, and prompt hardening.

Real-world production patterns for prompt engineering in 2026. Banking compliance prompts, SaaS onboarding flows, dev tool agent instructions, and the 12 most common anti-patterns to avoid.

How to test prompts in production. LLM-as-judge evaluation, prompt versioning strategies, A/B testing for prompts, regression testing pipelines, and automated evaluation frameworks for AI agents.