Enables AI agents to securely discover, invoke, and manage tools through a hardened MCP endpoint with protections like injection detection, circuit breakers, retry backoff, response caching, context-window limiting, and state snapshots.
Enables AI agents to safely call enterprise tools through a governed MCP gateway with permission enforcement, blast-radius controls, input validation, and a full audit trail for every invocation.
Enables agents to search a lightweight catalog, inspect permissions, lazily start trusted MCP servers, and call child tools without keeping all schemas in context. It also loads approved skills on demand and routes third-party additions through a human approval queue.
Enables an LLM to dynamically discover and call tools across multiple MCP servers (file, GitHub, SQL, Python execution) with authentication, rate limiting, and observability, supporting parallel execution and secure deployment.
