Enables secure interaction between LLMs and MCP tools by applying zero-trust security controls, including sensitive data masking, file system protection, and policy enforcement.
A transparent proxy and execution firewall that intercepts and audits AI agent tool calls against configurable security policies before forwarding them to downstream MCP servers. It provides safe execution environments with features like data redaction, anti-loop protection, and unified alert dispatching.
Enforces deterministic security policies on Model Context Protocol traffic between agents and remote MCP servers, including request validation, signed human approval, response-side credential blocking, prompt-injection flagging, and privacy-minimized auditing.
Runtime governance proxy for MCP tool calls. Inspects tool results for prompt injection and capability abuse before they reach your agent, blocking attacks that exploit the MCP trust boundary.