Compatible with every major AI agent and IDE
Create api key on Headscale (Tailscale Alternative)
Create a new API key
Create preauth key on Headscale (Tailscale Alternative)
Create a new pre-auth key
Create user on Headscale (Tailscale Alternative)
Create a new user in Headscale
Delete node on Headscale (Tailscale Alternative)
Remove a node from the Headscale network
Delete user on Headscale (Tailscale Alternative)
Delete a user from Headscale
Disable route on Headscale (Tailscale Alternative)
Disable a specific route
Enable route on Headscale (Tailscale Alternative)
Enable a specific route
Expire api key on Headscale (Tailscale Alternative)
Expire an API key
Expire node on Headscale (Tailscale Alternative)
Force expiration of a node session
Expire preauth key on Headscale (Tailscale Alternative)
Expire a pre-auth key
Get node on Headscale (Tailscale Alternative)
Get details for a specific node
List api keys on Headscale (Tailscale Alternative)
List all API keys
List nodes on Headscale (Tailscale Alternative)
List all nodes (machines) connected to Headscale
List preauth keys on Headscale (Tailscale Alternative)
List pre-auth keys
List routes on Headscale (Tailscale Alternative)
List all subnet routes and exit nodes
List users on Headscale (Tailscale Alternative)
List all users in Headscale
Move node on Headscale (Tailscale Alternative)
Move a node to a different user
Rename node on Headscale (Tailscale Alternative)
Rename a node in Headscale
How Vinkius protects your data
What happens if the underlying API rate limits my agent?
Our edge infrastructure automatically handles backoffs, queueing, and throttling. If an AI agent sends too many erratic requests, Vinkius manages the rate limits gracefully, ensuring your backend doesn't crash.
What if the AI ends up reading customer data or confidential information?
We have a built-in digital "bodyguard" called DLP (Data Loss Prevention). If a tool fetches data and the response contains social security numbers, credit cards, or personal customer info, Vinkius magically blocks and erases that information before it is delivered to the AI. The AI works only with what is strictly necessary, and your sensitive data never leaks.
Does the AI train on my tools or API data?
No. Vinkius enforces a strict Zero-Retention policy. Your data simply passes through our secure servers to complete the requested action and is instantly forgotten. Nothing you do here is ever stored, logged, or used to train any artificial intelligence.
Can I move a registered machine from one user to another using the AI?
Yes. Use the move_node tool by providing the Node ID and the target User name. The agent will reassign the machine to the new namespace immediately.
Automated Workflows using Headscale (Tailscale Alternative)
This integration supports direct MCP execution, enabling your chatbots to query and modify data within these specific environments.
The Future of vpn
The Headscale (Tailscale Alternative) server exposes documented endpoints for vpn. This allows ChatGPT and Cursor to interact with cloud infrastructure APIs seamlessly.
mesh network & AI Execution
Integrate Headscale (Tailscale Alternative) for AI-driven mesh network management. The MCP server structures the outputs required for Claude to analyze cloud infrastructure data.
Headscale (Tailscale Alternative). Runs on everything.
From IDE to framework. Every connection governed by Vinkius.
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
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