An embedded MCP gateway that sits in front of every agent, model, and tool call in your stack — governing and auditing the full agentic lifecycle from provisioning through execution to audit. Nothing an agent does is ungoverned, unlogged, or unapproved.
// every agent action passes the gateway const policy = { tool_calls: 'allow-listed', mcp_servers: 'registered, scoped', approvals: 'human-in-the-loop', audit_trail: 'full lifecycle', ungoverned_actions: 0, };
OWASP’s Top 10 for Agentic Applications catalogs the failure modes unique to systems that plan, use tools, and act with some degree of autonomy. Six are worth knowing cold — and each maps directly to a control the platform enforces.
Malicious content in a document, email, or web page the agent reads gets treated as an instruction, redirecting its objective without anyone touching a keyboard.
Parameter manipulation or chained tool calls turn an approved capability (send email, query a database, call an API) into an unapproved outcome.
Agents commonly inherit a human's or a service account's full permission set rather than a scoped one, turning a narrow task into broad cross-system access.
Agents that can generate and execute code or shell commands can be steered into running something destructive or exfiltrating data.
Poisoned entries in an agent's memory store or retrieval database bias its decisions in every future session, not just the current one.
Because agents are trusted actors in your workflows, a compromised one can operate for a long time before its behavior is flagged as abnormal.
An embedded MCP gateway brokers every tool and server connection an agent attempts — checked against policy before it executes, not after.
The platform enforces the same four-function framework NIST’s AI Risk Management Framework uses, and that U.S. regulators and state laws already point to when they ask for a “risk management program.”
A named owner per agent, a living production inventory, and a written agent policy distinct from your general AI policy.
Documented scope per agent, a risk tier based on what it can affect, and a flag for anything that counts as a consequential decision.
Real-time action monitoring, a tamper-evident audit trail, drift detection, and periodic red-teaming against agentic risk categories.
Human-in-the-loop approval gates, least-privilege scoped credentials, a one-click kill switch, and an incident runbook built for agent misbehavior.
The AI Agent Governance Playbook covers the same regulatory landscape, OWASP risk categories, and Govern/Map/Measure/Manage checklist this platform is built to enforce — plus a 12-point self-assessment scorecard.