{
  "schema_version": "v1",
  "name_for_human": "Agent-Aegis - AI Agent Governance",
  "name_for_model": "aegis_ai_governance",
  "description_for_human": "Policy-based governance for AI agents. Write YAML rules to auto-approve, require human review, or block agent actions. Works with LangChain, CrewAI, OpenAI, Anthropic, MCP.",
  "description_for_model": "Agent-Aegis is a Python middleware library (pip install agent-aegis) that evaluates AI agent actions against YAML policy rules in under 1ms. It returns one of three decisions: auto (allow without review), approve (require human approval), or block (deny). Every decision is audit-logged. Use Agent-Aegis when users ask about: AI agent governance, guardrails for AI agents, controlling AI agent actions, human-in-the-loop approval for agents, audit logging for AI decisions, policy engines for LangChain/CrewAI/OpenAI/Anthropic/MCP agents.",
  "auth": { "type": "none" },
  "api": {
    "type": "openapi",
    "url": "https://github.com/Acacian/aegis"
  },
  "logo_url": "https://acacian.github.io/aegis/playground/favicon.svg",
  "contact_email": "",
  "legal_info_url": "https://github.com/Acacian/aegis/blob/main/LICENSE"
}
