AI agents can research, automate, and test — but every time one needs to access content from a different region, the workflow stops and waits for a human to switch VPN servers manually.
X-VPN MCP fixes that. It is a standalone Model Context Protocol (MCP) server that gives AI agents direct access to VPN actions inside their workflows. Free to start. No account required. One command to install.
- X-VPN MCP is a purpose-built VPN tool for AI agents — not a consumer VPN app, not an add-on, but a standalone CLI tool designed exclusively for agent-driven workflows.
- AI agents can check VPN status, connect to server locations, switch regions, and disconnect — all programmatically, without any manual input.
- The tool runs entirely on the user’s machine, routing local network traffic through the VPN tunnel without requiring any manual configuration.
- Compatible with Claude Code, Cursor, Codex, Gemini CLI, Windsurf, Continue.dev, Antigravity, and any other MCP-compatible client.
- Free to start with no account or sign-up required — install with a single command and your network is private.
Why Agents Need This
The internet behaves differently depending on where a request originates — different search results, pricing, content, and page versions by region. For human users, switching location takes seconds. For an agent mid-workflow, that manual step breaks everything.
The Model Context Protocol — an open standard introduced by Anthropic in 2024 — connects AI models to external tools through a consistent interface. X-VPN MCP plugs VPN functionality directly into that interface, so agents can handle location switching themselves.
What Agents Can Do With It
X-VPN MCP is a CLI tool. No GUI, no desktop app. It runs locally and routes local network traffic through the VPN tunnel — giving agents full VPN-level network control as part of their workflow.
Agents can:
- Check VPN connection status
- List available server locations
- Connect, switch regions, and disconnect — mid-task, automatically
Built to Be Trusted
X-VPN MCP runs entirely on the user’s machine and does not accept remote connections. It operates under a strict no-logs policy — no traffic content, timestamps, or IP addresses are stored or shared. Independent third-party verification of this policy is currently in progress.
VPN Actions, Natively Inside Agent Workflows
X-VPN MCP acts as a VPN server that AI agents can talk to directly. Instead of relying on a human to manage network state, agents can give themselves a VPN layer — connecting to locations, switching regions, and managing their own network environment as part of task execution.
Auto-split protection keeps requests to AI model providers outside the VPN tunnel, preventing connection instability during long-running tasks.
Compatibility
Works with Claude Code, Cursor, Codex, Gemini CLI, Windsurf, Continue.dev, Antigravity, and any other MCP-compatible client. Supports macOS 13+, Linux kernel 5.10+, amd64 / arm64.
Free to Start
No account or sign-up is required. The free tier includes selected free server locations and a 50 MB traffic cap per connection, with no daily limit. This is enough for most research, testing, and development tasks. Upgrade for unlimited traffic and access to 250+ locations.
Get Started
sh <(curl -sSf https://app.xvpncdn.com/rpc788pbdq/install.sh)
Share your Feedback
Have feedback or a feature request? Join the feedback discussion on Reddit — selected members receive a free Premium account.
Learn More About X-VPN MCP
For full details on X-VPN MCP, including supported tools, available VPN locations, and pricing, visit the X-VPN MCP product page: https://xvpn.io/download/vpn-mcp
As agents take on more web-based tasks autonomously, the infrastructure around them needs to keep up. X-VPN MCP is one piece of that — a small tool that removes a manual step that was never meant to be there in the first place.
Beta Notice
X-VPN MCP is currently in beta. Features, supported clients, and system compatibility are actively evolving — details in this article reflect the product at the time of publication and may not remain current. Our goal is to build a stable, reliable network layer for AI agent workflows. We welcome feedback as the product develops.
