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YawLabs

@yawlabs/tailscale-mcp

by YawLabs

tailscale_create_org_tailnet

Create a new API-only tailnet in your organization and receive the tailnet details along with a newly issued OAuth client secret for direct API access.

Instructions

Create a new API-only tailnet in your organization. Returns the tailnet (id, displayName, orgId, dnsName, createdAt) AND a freshly-minted OAuth client for it.

SECURITY: the response body contains that OAuth client's secret verbatim, and it cannot be retrieved again. MCP clients commonly persist tool responses to logs and conversation transcripts; treat this response as sensitive.

Requires an OAuth client with the 'tailnets' scope -- an API key will not work. To then operate on the new tailnet, set TAILSCALE_OAUTH_TAILNET to its id and use an OAuth client with the 'all' scope.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
displayNameYesHuman-readable name for the new tailnet
organizationNoOrganization ID. Defaults to '-' (the organization owning the calling credentials).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv0.17.1

TDQS

A4.5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the annotations, the description discloses critical behavioral traits: the response contains an OAuth client secret verbatim, the secret cannot be retrieved again, and MCP clients may persist the response in logs. It also states the required auth scope. This is substantial value beyond the structured metadata.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core action, immediately states return value, then presents the security warning and prerequisites in clearly labeled sections. Every sentence adds necessary operational or security information with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description compensates by enumerating the returned fields (id, displayName, orgId, dnsName, createdAt) and warning about the secret. It also covers auth requirements and follow-up configuration, making it complete for correct invocation and handling of the result.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%: displayName and organization are already documented in the schema. The description does not add extra parameter-level detail, so it meets the baseline but does not exceed it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Create a new API-only tailnet in your organization.' It also clarifies the one-time OAuth client creation, which distinguishes this from the many list/update/delete tailnet siblings. An agent can tell exactly what operation this performs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear operational context: it requires an OAuth client with the 'tailnets' scope, explicitly says an API key will not work, and explains how to operate on the new tailnet afterward. It does not mention alternative tools or explicit when-not-to-use cases, but the context is specific enough for correct selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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