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Gatekeeper, Falco, and native RBAC govern Kubernetes resources. None of them model the layer above that: an AI agent acting on behalf of a named developer, making decisions based on a prompt, calling a tool chain before any K8s API call is ever made. mogenius does.
AI coding tools like Claude Code are sending a wave of builders into K8s clusters who are not infrastructure specialists. They command hundreds of agents in parallel. The impact amplification is real — and so is the damage potential.
The mogenius MCP server exposes the full Kubernetes toolchain to AI agents through a Model Context Protocol interface — governed by a purpose-built Kubernetes operator. Every tool call is validated against the policy for that identity and operation type before execution.
| Capability | Native K8s RBAC | Gatekeeper / OPA | Falco | mogenius |
|---|---|---|---|---|
| Resource-verb access control | ✓ | ✓ | ✗ | ✓ |
| Developer identity attribution on agent actions | ✗ | ✗ | ✗ | ✓ |
| Governance before the K8s API call (preventive) | ✗ | ✗ | ✗ | ✓ |
| Contextual policy (time, environment, approval) | ✗ | ✗ | ✗ | ✓ |
| Prompt-to-action audit trace | ✗ | ✗ | ✗ | ✓ |
| Workspace isolation at context level | ✗ | ✗ | ✗ | ✓ |
| Runtime anomaly detection | ✗ | ✗ | ✓ | Soon |
mogenius does not replace Gatekeeper or Falco — it governs the AI agent layer above them.
mogenius does not create a new compliance layer. It makes your existing AI agent operations auditable against the frameworks already in scope for your organization.
| Framework | Relevant Requirement | mogenius Capability |
|---|---|---|
| ISO 27001 | A.9.4 Access to systems and applications A.12.4 Logging and monitoring |
Role-based access per developer identity. Full JSON audit log of every agent action, attributable to the originating user. |
| SOC 2 Type II | CC6.1 Logical access controls CC7.2 System monitoring |
Preventive RBAC before the Kubernetes API call. Continuous action log available for auditor review at any time. |
| NIS2 | Art. 21 Access control, audit logging, incident handling | Developer-to-action attribution satisfies traceability requirements. Approval gates document authorization decisions for every high-risk operation. |
| DORA | Art. 9 ICT security controls and audit trails Art. 10 Detection capabilities |
Complete prompt-to-action trace per operation. Workspace isolation limits the blast radius of ICT incidents in Kubernetes environments. |
mogenius provides the technical controls. Certification against these frameworks remains the responsibility of your organization.
mogenius does not certify compliance on your behalf. The platform provides the technical controls that auditors and assessors look for under ISO 27001 (access control and logging under A.9.4 and A.12.4), SOC 2 Type II (logical access controls CC6.1 and system monitoring CC7.2), NIS2 (access management and audit trails under Art. 21), and DORA (ICT security controls and traceability under Art. 9 and Art. 10). Every agent action is attributed to a developer identity, logged with full context, and enforced by a preventive policy layer. Compliance teams get the evidence they need to demonstrate control over AI agent activity in production environments.
Organizations use the productivity benefits of AI agents in Kubernetes operations without losing control or compliance. mogenius positions itself as a security layer between AI agents and the cluster, every agent action is checked role-based, attributed, and preventively enforced before reaching the Kubernetes API. Teams adopt AI-powered workflows that remain auditable and meet existing governance requirements.
Organizations get a controlled AI integration in which platform governance applies instead of being bypassed. Many AI integrations give agents direct, unregulated access to the cluster, mogenius instead puts an operator and an MCP server between agent and Kubernetes API, checking every action against RBAC, workspace isolation, and approval gates. AI acts within the existing governance structure rather than around it.
Teams precisely define what an AI agent is allowed to access instead of opening the entire cluster. The Model Context Protocol (MCP) server is the controlled interface through which large language models get structured, role-based access to Kubernetes resources, it exposes only the tools and endpoints permitted for the respective role and logs every interaction. Organizations reduce the attack surface and keep full transparency over every agent action.
CISOs and platform teams can approve AI use because the control mechanisms reliably apply. mogenius offers AI RBAC with attribution of developer identity on every agent action, workspace isolation between teams, human-in-the-loop approval gates for high-risk operations, and a full JSON audit log of every agent action. Organizations can open even sensitive workflows to AI agents without crossing compliance boundaries.
Organizations choose the LLM that fits their use case and stay independent of a single vendor. mogenius supports any LLM reachable via API, such as OpenAI, Anthropic, Azure OpenAI, and Mistral, and on the Governed plan also self-hosted models such as Ollama for environments with strict data sovereignty requirements. Organizations in the DACH region and in regulated industries can use AI without handing over sensitive data to external services.
Organizations prevent uncontrolled production interventions by AI agents and secure their compliance posture. AI agents can start deployments, change scaling, and modify configurations, without governance these actions are neither traceable nor controllable, allowing compliance violations and production incidents. mogenius makes every AI action attributable, verifiable, and compliant, turning AI from a risk into a controlled productivity tool.
Deploy in under a week. Talk to us about your current agent setup.
Certifications & Memberships
mogenius is a CNCF Silver Member, a Certified Kubernetes product, and ISO 27001 certified via TÜV Saarland.