What each is for, where Docker MCP Gateway is strong, and how the two differ, capability by capability.
Docker, Inc. · Based on the vendor's public documentation, last reviewed .
Docker MCP Gateway
Docker's open-source MCP Gateway runs MCP servers in containers behind one endpoint. The paid Docker AI Governance tier adds Cedar policy for MCP tool calls, with rules on arguments and in-session confirmation.
The gateway is open source (MIT) and runs on developers' machines in Docker Desktop or as a CLI plugin for Docker Engine. AI Governance is a separate paid subscription, configured centrally in Docker Home or through an API, and Docker describes it as invite-only.
Vekri
Runtime authorization for AI agents. Vekri Gateway checks every tool call against a verified identity, a task scope and Cedar policy; privileged writes wait for a person's approval of the exact operation; a broker executes with credentials the agent never sees.
In Vekri's cloud, or self-hosted in your Kubernetes cluster with no connection to Vekri.
Side by side
| Capability | What it means | Vekri | Docker MCP Gateway |
|---|---|---|---|
| Decides each tool call inline | Every agent tool call is allowed or denied before it reaches the protected system. | Yes Vekri Gateway decides every MCP tool call sent through it before the broker executes it; a denied call never reaches the system. It is a boundary only when it is the only path to that system. | Documented AI Governance evaluates each MCP tool call against Cedar policy in the gateway before it runs. Listing tools is not checked by policy. [1] [2] |
| Verified workload identity | An agent running as a workload proves who it is with a credential the platform issued, not a shared key. | Yes Kubernetes projected service-account tokens, verified with TokenReview before Vekri issues a short-lived token for the run; every call is then authenticated. SPIFFE X.509-SVIDs from a configured trust bundle (no Workload API yet). | Not in public docs Developers sign in with an organization account. Attesting a workload's identity, for example with Kubernetes or SPIFFE, is not described. [5] |
| Employee agents use company SSO | Agents that employees run sign in as that employee, through the company identity provider. | Yes Vekri is the MCP authorization server for Claude Code and federates to your OpenID Connect provider. SAML sign-in is not available yet. | Documented Administrators can require developers to sign in with their organization account, managed through SAML and SCIM. [5] [2] |
| Task-scoped permissions from the server | What an agent may do is set per task by the server, not by the agent or its prompt. | Yes A run scope for workloads, or a protected access assignment for employees. The effective permission is always an intersection, never a widening. | Not in public docs Policy applies to an organization or a team. A scope issued by the server for each task is not described. [1] |
| Policy as code, deny by default | Decisions come from versioned policy, and anything not allowed is refused. | Yes Cedar over typed operations. Unknown operations and evaluation errors are denied, and a revision can be simulated before it is published. | Documented Cedar, denying by default, with forbid rules taking precedence. Rules can match tool names, tool annotations and call arguments. [1] |
| Approval of the exact operation | A person approves one specific operation, and the approval cannot be reused for another. | Yes Privileged writes wait for another person to approve that operation, bound to its digest, short-lived and single use, with separation of duties. | Partly A rule can ask the user to confirm one call in the session; the confirmation covers that request only. Docker describes it as an in-session confirmation rather than an out-of-band approval workflow. [1] |
| Agent never holds backend credentials | Secrets for the protected system stay out of the agent's reach. | Yes A broker executes with narrowly scoped Kubernetes or GitHub App credentials. Incoming tokens are never forwarded. | Documented MCP secrets stay on the host and are not injected into sandboxes; the gateway uses them to reach MCP servers. For other credentials, a proxy swaps placeholder values for the real keys in request headers. [3] |
| Audit evidence of decision and outcome | Each call leaves a durable record of what was decided and what happened. | Yes Intent is recorded durably before execution and the outcome after; an uncertain outcome is never retried blindly. | Documented Each policy evaluation is recorded with the user, the session and the rule that applied, and can be streamed to a SIEM. [2] |
| AI agents on workstations | Finds AI coding agents and other AI applications on employee devices, and watches or controls what they do there. | Partly Vekri Endpoint discovers coding agents, desktop and IDE AI apps, local models and their MCP servers on macOS and Linux, and its local MCP gateway decides each MCP tool call sent through it (Claude Code verified connecting; tool calls verified with an MCP client library). On macOS, a network gateway mediates MCP requests to approved remote servers, and agent control stops AI agents the organization has not allowed. Hooks observe built-in tools without blocking them; Windows is not supported. | Partly Docker Sandboxes run Claude Code, Codex and other agents on the developer's machine under governance. Discovering agents already installed outside Docker is not described. [8] [5] |
| Prompt and output inspection | Detects prompt injection or sensitive data in what models read and write. | Partly Tool results on Vekri Gateway and the local MCP gateway are inspected for prompt injection before the agent reads them; sensitive-data categories are detected on the device, off by default. Browsers and file uploads are not inspected. | Partly The gateway can block secrets in tool traffic, on by default. Prompt-injection detection is not described. [4] |
| Systems covered | Which systems, platforms or agents the product works with. | Kubernetes and GitHub, with GitLab, PostgreSQL, MySQL, MongoDB, Slack, Jira, Linear, Asana, ClickUp, monday.com, HubSpot, Pipedrive, Zendesk, Freshdesk and custom OpenAPI connectors in preview. | A catalog of more than 300 verified MCP server images, run in containers on developers' machines and in Docker Sandboxes. |
| Deployment | How the product is delivered. | In Vekri's cloud, or self-hosted in your Kubernetes cluster with no connection to Vekri. | The gateway is open source (MIT) and runs on developers' machines in Docker Desktop or as a CLI plugin for Docker Engine. AI Governance is a separate paid subscription, configured centrally in Docker Home or through an API, and Docker describes it as invite-only. |
Every agent tool call is allowed or denied before it reaches the protected system.
An agent running as a workload proves who it is with a credential the platform issued, not a shared key.
Agents that employees run sign in as that employee, through the company identity provider.
What an agent may do is set per task by the server, not by the agent or its prompt.
Decisions come from versioned policy, and anything not allowed is refused.
A person approves one specific operation, and the approval cannot be reused for another.
Secrets for the protected system stay out of the agent's reach.
Each call leaves a durable record of what was decided and what happened.
Finds AI coding agents and other AI applications on employee devices, and watches or controls what they do there.
Detects prompt injection or sensitive data in what models read and write.
Which systems, platforms or agents the product works with.
How the product is delivered.
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