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Vekri vs Teleport

What each is for, where Teleport is strong, and how the two differ, capability by capability.

Teleport · Based on the vendor's public documentation, last reviewed .

At a glance

Teleport

Teleport is an infrastructure access platform for people and machines. Its MCP access proxies MCP servers, allows or denies each tool by role, records every request, and issues short-lived credentials to users and bots.

Community Edition is free and open source. Enterprise is self-hosted with a paid licence or run by Teleport as Enterprise Cloud. The feature matrix lists MCP access in all three editions.

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.

Where Teleport is strong

Teleport is a mature access platform that already brokers servers, Kubernetes, databases and applications, with single sign-on, short-lived certificates and session recording. Its MCP access is in every edition, including the open-source one, supports stdio servers, allows tools by role with deny taking precedence, and records each request. Machine & Workload Identity attests bots with platform tokens and issues SPIFFE identities, which Vekri supports only in part.

Where Vekri differs

Teleport grants MCP access through roles that allow whole tools, and its Access Requests grant a role for a period. Vekri issues a scope for each task, decides typed operations against Cedar policy, and has another person approve a privileged write, bound to that exact operation and usable once, before its broker executes it with credentials the agent never sees.

Side by side

Vekri and Teleport, capability by capability.

"Not in public docs" means we could not find it in the vendor's public documentation on the review date, not that it is missing.

Decides each tool call inline

Every agent tool call is allowed or denied before it reaches the protected system.

VekriYes
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.
TeleportDocumented
Teleport proxies MCP traffic and checks each tool call against the user's roles. A denied call is blocked and recorded. [1] [2] [3]

Verified workload identity

An agent running as a workload proves who it is with a credential the platform issued, not a shared key.

VekriYes
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).
TeleportDocumented
Bots join with platform proof, such as a Kubernetes service account token, and receive short-lived credentials they can use for MCP access. Teleport also issues SPIFFE SVIDs to workloads. [6] [7] [5]

Employee agents use company SSO

Agents that employees run sign in as that employee, through the company identity provider.

VekriYes
Vekri is the MCP authorization server for Claude Code and federates to your OpenID Connect provider. SAML sign-in is not available yet.
TeleportDocumented
People sign in with tsh, through single sign-on, and their MCP clients use that session. Enterprise editions support OIDC, SAML and GitHub; Community Edition supports GitHub. [8] [9]

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.

VekriYes
A run scope for workloads, or a protected access assignment for employees. The effective permission is always an intersection, never a widening.
TeleportPartly
Just-in-time Access Requests grant extra roles for a limited time, typically for a whole MCP server. A scope issued by the server for each agent task is not described. [10] [9]

Policy as code, deny by default

Decisions come from versioned policy, and anything not allowed is refused.

VekriYes
Cedar over typed operations. Unknown operations and evaluation errors are denied, and a revision can be simulated before it is published.
TeleportDocumented
Roles list allowed and denied MCP tools by name, glob or regular expression. No tool is allowed unless listed, deny takes precedence, and rules on tool arguments are not described. [2]

Approval of the exact operation

A person approves one specific operation, and the approval cannot be reused for another.

VekriYes
Privileged writes wait for another person to approve that operation, bound to its digest, short-lived and single use, with separation of duties.
TeleportPartly
Reviewers approve Access Requests, which grant access to an MCP server for a period, often hours. Approval of a single tool call is not described. [10]

Agent never holds backend credentials

Secrets for the protected system stay out of the agent's reach.

VekriYes
A broker executes with narrowly scoped Kubernetes or GitHub App credentials. Incoming tokens are never forwarded.
TeleportDocumented
Clients hold short-lived Teleport credentials, and Teleport sends the MCP server its own signed JWT identifying the user and roles. [4] [7]

Audit evidence of decision and outcome

Each call leaves a durable record of what was decided and what happened.

VekriYes
Intent is recorded durably before execution and the outcome after; an uncertain outcome is never retried blindly.
TeleportDocumented
Each MCP request, including denied ones, is recorded as an audit event carrying the JSON-RPC message, with the tool name and arguments. [3] [9]

AI agents on workstations

Finds AI coding agents and other AI applications on employee devices, and watches or controls what they do there.

VekriPartly
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.
TeleportNot in public docs
Agent visibility and discovery is listed as in progress in Teleport's Agentic Identity Framework. Discovering coding agents on workstations is not described as available. [11]

Prompt and output inspection

Detects prompt injection or sensitive data in what models read and write.

VekriPartly
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.
TeleportNot in public docs
Inspecting prompts or tool output is not described in the MCP access documentation. [1]

Systems covered

Which systems, platforms or agents the product works with.

Vekri
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.
Teleport
Servers, Kubernetes clusters, databases, applications and MCP servers over stdio, SSE or streamable HTTP, used from clients that tsh configures, such as Claude Desktop and Cursor.

Deployment

How the product is delivered.

Vekri
In Vekri's cloud, or self-hosted in your Kubernetes cluster with no connection to Vekri.
Teleport
Community Edition is free and open source. Enterprise is self-hosted with a paid licence or run by Teleport as Enterprise Cloud. The feature matrix lists MCP access in all three editions.

Using both

Teleport can keep governing how people and machines reach servers, databases and clusters, while Vekri governs the agent tool calls to Kubernetes and GitHub that need a task scope and an approval of the exact operation.

More comparisons

Agent identity and access

All comparisons

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See Vekri with your own AI applications, agents and systems.

Talk to us about the AI your organization uses, the systems agents reach and how you deploy: in Vekri's cloud, or inside your own Kubernetes cluster.