Axtary: Content Authorization System for AI Agents

Axtary addresses a growing concern in AI agent deployment: the tension between capability and control. As agents take on sensitive tasks—committing code, updating infrastructure, posting to company channels, querying databases—the permission model becomes critical. Traditional tool-based access control grants broad permissions (e.g., "use Slack" or "write to GitHub") with limited visibility into what each invocation actually does. Axtary inverts this by enforcing authorization at the payload level: not "can the agent use GitHub?", but "is this exact pull request diff what the human reviewed and approved?"

The platform's architecture separates concerns deliberately. Local enforcement and credential storage mean sensitive operations never transit a central server in the approval path; the hosted control plane only orchestrates policy, review workflows, and audit trails. This design reduces the blast radius if the hosted service is compromised—an attacker cannot directly trigger privileged actions without local verification. Axtary's support for both MCP (Model Context Protocol) servers and native connectors to mainstream platforms (GitHub, Slack, AWS, Google Cloud) suggests it aims to fit into existing AI agent runtimes without requiring architectural rewrites.