ngrok MCP Server for AutoGenGive AutoGen instant access to 7 tools to List Api Keys, List Endpoints, List Https Edges, and more
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add ngrok as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.
Ask AI about this MCP Server for AutoGen
The ngrok MCP Server for AutoGen is a standout in the Loved By Devs category — giving your AI agent 7 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with McpWorkbench(
server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
transport="streamable_http",
) as workbench:
tools = await workbench.list_tools()
agent = AssistantAgent(
name="ngrok_agent",
tools=tools,
system_message=(
"You help users with ngrok. "
"7 tools available."
),
)
print(f"Agent ready with {len(tools)} tools")
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About ngrok MCP Server
Connect your ngrok account to any AI agent and take full control of your ingress infrastructure through natural conversation.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use ngrok tools. Connect 7 tools through Vinkius and assign role-based access. a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.
What you can do
- Endpoints & Edges — List all active public URLs (ephemeral, edge, or cloud) and inspect HTTPS edges for advanced routing configurations
- Security & Access — Audit IP policies and restrictions applied to your dashboard, API, or agents to ensure secure access
- Domain Management — Retrieve all custom domains reserved for your applications directly from the ngrok cloud
- Credential Management — List API keys used for authentication and manage secure vaults for sensitive values
- Infrastructure Visibility — Get a bird's-eye view of your entire tunneling setup without leaving your terminal or chat interface
The ngrok MCP Server exposes 7 tools through the Vinkius. Connect it to AutoGen in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 7 ngrok tools available for AutoGen
When AutoGen connects to ngrok through Vinkius, your AI agent gets direct access to every tool listed below — spanning tunneling, ingress, api-gateway, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.
List api keys on ngrok
List ngrok API keys
List endpoints on ngrok
List ngrok endpoints
List https edges on ngrok
List ngrok HTTPS edges
List ip policies on ngrok
List ngrok IP policies
List ip restrictions on ngrok
List ngrok IP restrictions
List reserved domains on ngrok
List ngrok reserved domains
List vaults on ngrok
List ngrok vaults
Connect ngrok to AutoGen via MCP
Follow these steps to wire ngrok into AutoGen. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.
Install AutoGen
pip install "autogen-ext[mcp]"Replace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenIntegrate into workflow
Explore tools
Why Use AutoGen with the ngrok MCP Server
AutoGen provides unique advantages when paired with ngrok through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use ngrok tools to solve complex tasks
Role-based architecture lets you assign ngrok tool access to specific agents. a data analyst queries while a reviewer validates
Human-in-the-loop support: agents can pause for human approval before executing sensitive ngrok tool calls
Code execution sandbox: AutoGen agents can write and run code that processes ngrok tool responses in an isolated environment
ngrok + AutoGen Use Cases
Practical scenarios where AutoGen combined with the ngrok MCP Server delivers measurable value.
Collaborative analysis: one agent queries ngrok while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from ngrok, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using ngrok data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process ngrok responses in a sandboxed execution environment
Example Prompts for ngrok in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with ngrok immediately.
"List all active ngrok endpoints."
"Show me the reserved domains in my account."
"What IP policies are currently configured?"
Troubleshooting ngrok MCP Server with AutoGen
Common issues when connecting ngrok to AutoGen through Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"ngrok + AutoGen FAQ
Common questions about integrating ngrok MCP Server with AutoGen.
How does AutoGen connect to MCP servers?
Can different agents have different MCP tool access?
Does AutoGen support human approval for tool calls?
Explore More MCP Servers
View all →
Orderry
12 toolsManage your repair shop, orders, and inventory with Orderry and AI agents.

Unsplash Alternative
10 toolsManage your visual discovery — search photos, users, and collections via AI.

Loopio
8 toolsConnect your Loopio RFP platform to AI — search approved answers, manage proposal projects, and automate questionnaire responses naturally via chat.

XML JSON Converter
2 toolsParse legacy systems easily. Deterministically convert massive XML, SOAP, or RSS feeds into clean JSON (and back) without LLM hallucinations.
