Docker AI Governance
AI governance for every agent
Works with every AI tool your team uses
One engine.
Three layers of control.
Network and filesystem control. Enforced, not advised.
Define allow and deny rules for domains, IPs, and CIDRs. Set filesystem mount rules with read-only or read-write scope. Enforcement happens at the proxy and mount level.
Control which tools agents can use. Org-wide, by default.
Admins control which MCP servers and tools are available organization-wide. Unapproved servers are blocked by default and every MCP call flows through the same policy engine.
The proof CISOs need to confidently approve AI.
Every policy evaluation generates a structured event with user identity, timestamp, session context, and triggering rule. Export to your existing SIEM and compliance systems. Get full traceability, zero blind spots.
Define once. Propagate everywhere.
supabase / mcp-server
Developer Machines Live
Machines updated
AI governance for every stakeholder.
Approve AI. Not just permit it.
Full auditability and centralized policy gives you the evidence to confidently sign off on agent adoption across the organization.
Define once. Enforce everywhere.
Policy is set centrally and propagates on developer authentication. No per-machine config. Scales through your existing SAML and SCIM IdP.
Full speed. Zero friction.
Governance runs in the background. Agents work the way they’re supposed to, autonomously, on the tools you already use.
Most tools cover one slice.
Docker covers the whole agent.
|
Network |
Filesystem |
MCP |
On the laptop |
|
|---|---|---|---|---|
Docker AI GovernanceSandbox + MCP, one console, on the laptop your employees already use. |
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MCP-only gatewaysNetwork and filesystem out of scope by design. |
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Agent meshRuns in the data plane. Doesn’t reach the laptop. |
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Remote dev environmentsCovers everything — after migrating every dev off their laptop. |
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