"Kyverno policy examples and documentation" matching MCP servers:

Drop-in stdio interceptor that gates MCP tools/call requests through a YAML policy (block / require_approval / audit / budget cap) before they reach the real server. The same policy file is reused by @jamjet/claude-code-hook and @jamjet/openai-guardrail, so one rule set covers Claude Desktop, Cursor, OpenAI Agents, and custom clients.

A local-first MCP policy gateway that provides a four-step workflow (plan, approve, execute, read) for a single Apify fixture Actor, enforcing a fixed policy and sanitizing results. It does not call Apify and is designed as a policy control plane.

Enables policy-governed MCP interactions with deterministic authorization, tenant isolation, minimized PII exposure, and human approval gates for sensitive mutations, while producing structured audit events.

A governance and policy enforcement gateway for MCP servers that provides hard guardrails, dynamic parameter bounds, human-in-the-loop approvals, and audit telemetry.

Enables AI agents and MCP clients to safely access upstream MCP servers through centralized policy enforcement, including allow/deny/approval decisions, schema pinning, circuit breakers, and audit logging.

Analyzes application code locally to automatically generate baseline AWS IAM identity-based policies by detecting AWS SDK calls in Python, Go, and TypeScript applications. Helps AI coding assistants quickly create IAM permissions that can be refined as applications evolve.

Proxies MCP traffic between a client and a downstream server to enforce runtime policies on tool declarations, call arguments, and results, including allowlisting, sandboxing, secret and egress controls, and injection detection. It also includes a deterministic benchmark for measuring which security controls stop which attacks.

An authorizing reverse proxy for MCP servers that enforces per-call policy rules on tool arguments with audit logging, dry-run, and rate limiting.

Converts natural language security requirements into validated Cerbos YAML policies with automated testing and red-team analysis, enabling AI governance with zero-trust guardrails for tool calls, data access, and compliance frameworks.

Per-agent-pair IAM for A2A, enabling policy definition and enforcement for agent-to-agent calls with EU AI Act compliance.

An MCP server that provides natural language interaction with Google's Policy Troubleshooter API, allowing users to troubleshoot access denied errors and analyze IAM policies.

Compliance and guardrails infrastructure for AI agents, enabling safe operations within regulatory boundaries like GDPR and EU AI Act.

Provides real-time policy enforcement for AI coding agents by intercepting and validating their actions against organizational standards like naming conventions, security policies, and compliance rules before execution. Prevents violations through immediate feedback and auto-correction suggestions.

Pre-execution safety layer for autonomous agent wallets. Risk scoring, transaction simulation, and policy enforcement via MCP.

PolicyPulse connects your AI assistant directly to your Kubernetes policy engines. Instead of switching between three dashboards and two CLIs, you ask in plain English and get answers enriched with CIS Kubernetes, PCI-DSS, NIST 800-53, and SOC 2 framework references.

This MCP server implements VariousPolicies according to CSA BOD 25-01 requirements for Microsoft 365 cloud services

Enables AI assistants to search and retrieve information from the REMnux malware analysis toolkit documentation, allowing users to ask questions about reverse-engineering tools and get accurate, up-to-date answers from the live documentation.

An MCP server providing role-based access control for HR policies, exposing tools to list, retrieve, and check access to policy sections while filtering sensitive data by role.

A FastMCP server template with full MCP authentication via Descope, designed for easy deployment on Render. It provides a foundation for building secure, authenticated MCP servers with scope-based access control.

Enables AI agents to discover and execute tools via a secure MCP server with JWT authentication, RBAC, rate limiting, and audit logging.