MCP security, agentic AI governance, SOPs, approval gates, and OWASP agentic top 10. 12 articles, written by the engineers building AI App Lab.
OWASP Top 10 for Agentic AI Applications (2026): 10 critical risks from agent goal hijack to rogue agents. Real incidents, attack examples, mitigations, and enterprise defense strategies for autonomous AI systems.
What is MCP (Model Context Protocol)? Anthropic's open standard for connecting AI agents to data sources and tools. Architecture, primitives (tools, resources, prompts), transport, and enterprise use cases.
AI agent company knowledge: enterprise brain architecture, knowledge graphs, RAG integration, GraphRAG, multi-source ingestion (SharePoint, Confluence, Jira), RBAC, self-hosted knowledge hub, and MCP server patterns.
Agentic AI governance: policy-as-code guardrails, human-in-the-loop approval workflows, EU AI Act compliance (Articles 9, 14, 12), NIST AI RMF alignment, circuit breakers, kill switches, and audit trails for enterprise autonomous AI.
MCP security: 40+ CVEs in 2026, attack vectors (tool poisoning, prompt injection, rug pulls, OAuth confusion), OWASP cheat sheet defenses, OAuth 2.1, input validation, and enterprise hardening for MCP servers.
AI SOP automation: encode standard operating procedures as executable AI agent workflows. SOP-to-agent pipeline, cross-platform orchestration, decision trees, human handoff, RAG integration, and enterprise implementation patterns.
RAG to actuation pipeline: agentic RAG that retrieves, reasons, decides, and acts. Multi-hop retrieval, tool calling, policy-to-action workflows, diagnostic resolution, and enterprise patterns for retrieval-to-execution pipelines.
AI agent cron scheduling: heartbeat mechanism, cron expressions for autonomous agents, three-layer architecture (heartbeat, cron, memory), scheduled reports, monitoring, retry policies, and enterprise deployment patterns.
AI agent action approval: human-in-the-loop workflows for high-risk agent actions. Three-tier policy (allow/deny/escalate), multi-level escalation, timeout auto-deny, Slack approval, audit trails, and enterprise implementation patterns.
AI wiki generation: agents auto-generate structured, interlinked wiki pages from raw documents, code, tickets, and meetings. Multi-agent processing, MRP pipeline, knowledge graphs, CI/CD integration, and enterprise wiki automation.
Build and deploy MCP servers for Claude Desktop, Claude Code, and Cursor: Python FastMCP and TypeScript SDK, stdio vs Streamable HTTP transport, OAuth 2.1 auth, production deployment, and enterprise tool integration.
AI event-triggered automation: webhook-driven agent workflows, event stream processing (Kafka, EventBridge), real-time triggers, HMAC verification, dead letter queues, and enterprise event-driven architecture patterns.