MCP Security Threat Model for Production Systems
A practical threat model for MCP hosts, clients, servers, tools, credentials, model context, and downstream systems.
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Everything required to move AI agents from prototypes into secure, observable, reliable, scalable production systems.
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MCP Tool Permissions and Least Privilege
A practical permission model for controlling which MCP tools users and agents can discover, call, and approve.
MCP Prompt Injection, Tool Poisoning, and Data Exfiltration
A defensive guide to prompt injection, tool poisoning, confused-deputy risks, and data exfiltration in MCP systems.
Deploy and Observe a Remote MCP Server
A production deployment guide for remote MCP servers covering network boundaries, identity, scaling, observability, and rollback.
MCP Error Handling: Timeouts, Retries, and Cancellation
A reliability guide to MCP errors, deadlines, retries, cancellation, progress, idempotency, ambiguous writes, and observable recovery.
MCP Authentication and Authorization Explained
A production-focused guide to authenticating MCP clients and authorizing users, tools, resources, tenants, and downstream actions.
Designing Agent Fallbacks and Graceful Degradation
Keep an agent safely useful when models, tools, data, or specialists fail—without fabricating success or silently weakening controls.
Production Monitoring for AI Agents
Turn traces, metrics, logs, and evaluations into selected production signals, thresholds, dashboards, and actionable alerts.
Caching Strategies for AI Agent Systems
Reuse expensive results only when identity, freshness, authorization, and side-effect semantics make reuse safe.
Model Routing for AI Agents
Choose models by task requirements, policy, quality, latency, and cost instead of sending every step to one default.