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Secure LLM and MCP tool interactions with zero-trust controls and policy enforcement.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Security Guard MCP" yet — see the docs or source repo.
Before calling MCP tools, enable sensitive data masking and output inspection. Detect and block API keys, email addresses, ID numbers, and internal paths while keeping the task usable.
A sanitized request or response with a note describing which sensitive field types were blocked or replaced.
Configure file system protection for an MCP tool: allow reads only in /workspace/project, deny access to home folders, system directories, and secret files, and log violations.
A restricted access policy that denies unauthorized operations and returns audit log details for violations.
Audit the current zero-trust policy for LLM and MCP tool interactions. Verify tool permissions, data exposure risks, and enforcement points, then provide hardening recommendations.
A security audit summary with risk findings, policy gaps, and actionable hardening recommendations.
Perform file tasks, manage npm packages, and check configuration security via MCP.
Continuously scan and monitor MCP operations for agent-tool security risks.
Enforce permissions, approvals, sanitization, and audit for AI agent MCP calls.
Protect MCP-connected agents with PII redaction, rate limits, and policy enforcement.
Secure MCP servers with policy checks, redaction, access control, and audit logs
Intercept and block MCP tool calls with YAML policies for safer AI agents.