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
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.