Enables AI agents to securely perform privileged actions like creating GitHub issues by minting short-lived, single-purpose tokens on demand, with policy enforcement and audit logging.
Enables controlled AI-agent access to enterprise-shaped tools with a deny-by-default gated write path, human approval, dry-run execution, and append-only audit logging.
Enables secure enterprise AI agents to access internal tools like GitHub, Gmail, Calendar, file systems, databases, and knowledge bases through the Model Context Protocol, with built-in security, audit, and observability.
Connects AI assistants to GitHub repositories, pull requests, issues, commits, and code search while enabling repository visibility controls, CI/CD monitoring, sandboxed local filesystem access, and code quality/security analysis.
Enables AI agents to make authenticated API calls and run commands with secrets injected, while keeping credentials completely hidden from the model, with policy enforcement, grants, and audit logging.
Enables AI agents to securely call enterprise MCP tools with tenant-scoped RBAC, human approvals, audit logging, and multi-tool workflows across customer, order, document, and ticket data.