Developer infrastructure for controlling AI agent actions before they execute, including tool permissions, MCP enforcement, approvals, parameter policies, and audit logs.
Enforra is building runtime control for AI agents.
As agents move from chat responses into real actions across tools, APIs, files, databases, SaaS platforms, MCP servers, and internal workflows, teams need better controls before actions execute.
We believe system prompts are not enough as a security boundary for production agents. Agents need runtime permissions, policy enforcement, parameter-level controls, human approval workflows, and audit logs.
On DEV, we write about AI agent security, MCP enforcement, tool-call governance, runtime policy, approval workflows, prompt failures, and controlled autonomy.
