zrok-mcp
Enables AI agents to manage zrok tunnels, shares, and access programmatically through environment management, share creation/deletion/listing, and access control actions.
README
zrok-mcp
An MCP server for zrok — the open-source secure sharing platform built on OpenZiti. Lets AI agents manage zrok tunnels, shares, and access programmatically.
Supports three transports: stdio (local), streamable-http and SSE (remote/Bifrost).
Tools
Each tool uses an action parameter to select the operation — no need to remember many tool names.
zrok_env — Environment management
| Action | Description |
|---|---|
status |
Check environment status (enabled, API endpoint, identity) |
enable |
Enable the zrok environment with an account token |
disable |
Disable the current zrok environment |
zrok_share — Share management
| Action | Description |
|---|---|
create |
Create a public or private share |
delete |
Delete a share by token |
list |
List all shares with optional filters |
zrok_access — Access management
| Action | Description |
|---|---|
create |
Create access to a private share |
delete |
Remove access to a share |
list |
List all accesses with optional filters |
Requirements
- Python 3.10+
- zrok2 Python SDK
- A zrok account and enabled environment
Install
cd zrok-mcp
pip install -e .
Run
Transport is selected via the ZROK_MCP_TRANSPORT environment variable (default: stdio).
| Transport | Use case |
|---|---|
stdio |
Local clients (Claude Desktop, Cursor, Crush) |
streamable-http |
Remote / Bifrost gateway (recommended) |
sse |
Remote / Bifrost gateway (legacy SSE) |
STDIO (default)
zrok-mcp
Streamable HTTP (remote)
ZROK_MCP_TRANSPORT=streamable-http ZROK_MCP_PORT=8000 zrok-mcp
Docker (remote)
docker build -t zrok-mcp .
docker run -p 8000:8000 -v ~/.zrok2:/root/.zrok2 zrok-mcp
With MCP Inspector
mcp dev src/zrok_mcp/server.py
Environment Variables
| Variable | Default | Description |
|---|---|---|
ZROK_MCP_TRANSPORT |
stdio |
Transport: stdio, streamable-http, or sse |
ZROK_MCP_HOST |
0.0.0.0 |
Bind host (HTTP/SSE transports) |
ZROK_MCP_PORT |
8000 |
Bind port (HTTP/SSE transports) |
Configuration
Claude Desktop (stdio)
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"zrok": {
"command": "uv",
"args": ["--directory", "/path/to/zrok-mcp", "run", "zrok-mcp"]
}
}
}
Cursor / Crush (stdio)
Add to your crush settings or MCP config:
{
"zrok": {
"command": "uv",
"args": ["--directory", "/path/to/zrok-mcp", "run", "zrok-mcp"]
}
}
Bifrost AI Gateway (streamable-http)
- Deploy zrok-mcp as a remote HTTP server (Docker, Railway, etc.)
- In the Bifrost Web UI, go to MCP Gateway → New MCP Server
- Select HTTP as the connection type
- Enter the URL:
http://your-zrok-mcp-host:8000/mcp - Set
tools_to_executeto["*"](or filter as needed)
Or via config file:
{
"mcp": {
"mcp_clients": [
{
"name": "zrok",
"connection_type": "http",
"connection_string": "http://your-zrok-mcp-host:8000/mcp",
"tools_to_execute": ["*"]
}
]
}
}
For SSE transport, use connection_type: "sse" and connection_string: "http://your-zrok-mcp-host:8000/sse".
Example Usage
Once configured, your AI agent can do things like:
"Share my local server on port 3000 publicly via zrok"
The agent will call zrok_share(action="create", target="http://localhost:3000") and return the public URL.
"List all my zrok shares"
The agent will call zrok_share(action="list") and show token, mode, target, and endpoints.
"Create a private TCP tunnel for my database on port 5432"
The agent will call zrok_share(action="create", share_mode="private", backend_mode="tcpTunnel", target="localhost:5432").
License
MIT
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