MCP Risk Management: Failure Modes and Blast Radius
Map how MCP-connected Claude agents fail, score tool blast radius, and apply least-privilege, hard caps, and kill switches to contain the worst cases.
Agentic AI, LLM engineering, and the models behind modern automation — multi-agent systems, LLM evaluation and comparisons, RAG, fine-tuning, AI infrastructure, security, and production AI engineering.
From the blog
Map how MCP-connected Claude agents fail, score tool blast radius, and apply least-privilege, hard caps, and kill switches to contain the worst cases.
Model Context Protocol reshapes AI team roles. The new skills engineers, ops, and leaders must learn to ship Claude agents that use MCP well in 2026.
How to scale Model Context Protocol from one team to many with Claude — registries, ownership, versioning, and platform patterns that avoid chaos.
An honest guide to when Model Context Protocol is right with Claude and when a simpler alternative wins — real trade-offs, not hype.
The governance, trust, and safety controls leaders need around Model Context Protocol and Claude before agents touch production at scale.
How engineering teams actually adopt Model Context Protocol with Claude — the norms, habits, and change management that make MCP stick.
A concrete cost model for Model Context Protocol with Claude — where engineering time and token savings come from, and how to measure payback.
A rollout playbook for moving workflows onto Model Context Protocol agents with Claude: shadow mode, human-in-the-loop, staged autonomy, and safe rollback.
Build an eval loop for Model Context Protocol agents on Claude: measure tool use, score with LLM judges, and gate every release behind a passing suite.