Routes natural language queries to appropriate MCP tools and planners with high-precision semantic matching and safety guardrails. Supports multi-intent detection, task planning, and strict role-based filtering to prevent misexecution or unauthorized access.
A governance and control layer for MCP tools that manages tool requests as intents through policy-based approval, queuing, or blocking. It enables secure human oversight and audit trails for consequential agent actions across platforms like Claude Desktop and Cursor.
Governed MCP gateway that lets AI agents call tools with policy enforcement, prompt-injection screening, a kill-switch, and tamper-evident signed audit logs.
Governance engine for MCP tool calls, providing deterministic rule enforcement to block destructive actions like SQL drops, shell commands, and file system modifications before execution.
IntentFence is an open spend and action policy gate for autonomous AI that evaluates tool call constraints like scope, cost, data-retention, and approval, returning decisions such as safe_to_proceed, needs_review, or denied, and provides an MCP server endpoint at /mcp.
