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Public Ingress

OrganizationPopular
vellum-ai
public-ingress

Set up and manage ngrok-based public ingress for local assistants; do not use this in managed mode when platform callback routing is available

Overview

Publishervellum-ai
Repositoryvellum-assistant
Skill namepublic-ingress
Stars
1.4K
Forks
208
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by vellum-ai on GitHub. Read the source before you install it.

Installation

Install the Public Ingress AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/vellum-ai/vellum-assistant/tree/main/skills/public-ingress
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/vellum-ai/vellum-assistant.git /tmp/vellum-assistant
mkdir -p .claude/skills
cp -r /tmp/vellum-assistant/skills/public-ingress .claude/skills/public-ingress
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Public Ingress in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Public Ingress on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Public Ingress is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

You are setting up and managing a public ingress tunnel so that external services (Telegram webhooks, OAuth callbacks, etc.) can reach the local Vellum gateway. This skill uses ngrok to create a secure tunnel and persists the public URL as ingress.publicBaseUrl.

If managed platform callback routing is available, stop and do not continue with ngrok. In platform-managed deployments, Telegram/Twilio/OAuth callback routing should use the platform callback route flow instead of local public ingress.

Overview

The Vellum gateway listens locally and needs a publicly reachable URL for:

  • Telegram webhook delivery
  • Google/Slack OAuth redirect callbacks
  • Any other inbound webhook traffic

This skill installs ngrok, configures authentication, starts a tunnel, discovers the public URL, and saves it to the assistant's ingress config.

On Windows, use the PowerShell blocks instead of the POSIX ones.

Step 0: Reject Managed Callback Environments

Check whether managed platform callback routing is available:

bash
assistant platform status --json

If the result shows isPlatform: true and available: true, stop here. Tell the user that this assistant should use the platform callback route flow instead of ngrok, and do not install or start ngrok.

Step 1: Check Current Ingress Status

First, check whether ingress is already configured:

bash
assistant config get ingress.publicBaseUrl
assistant config get ingress.enabled

The local gateway URL is available as the $INTERNAL_GATEWAY_BASE_URL environment variable (defaults to http://127.0.0.1:7830).

The commands return:

  • ingress.publicBaseUrl - currently configured public ingress URL (if any)
  • ingress.enabled - whether ingress is enabled

If publicBaseUrl is already set and the tunnel is running (check via curl -s http://127.0.0.1:4040/api/tunnels), tell the user the current status and ask if they want to reconfigure or if this is sufficient.

On Windows, check the tunnel with:

powershell
Invoke-RestMethod http://127.0.0.1:4040/api/tunnels

Step 2: Install ngrok

Check if ngrok is installed:

bash
ngrok version

If not installed, install it:

macOS (Homebrew):

bash
brew install ngrok/ngrok/ngrok

Windows (Microsoft Store via WinGet):

powershell
winget install ngrok -s msstore

Linux (snap):

bash
sudo snap install ngrok

Linux (apt - alternative):

bash
curl -sSL https://ngrok-agent.s3.amazonaws.com/ngrok.asc | sudo tee /etc/apt/trusted.gpg.d/ngrok.asc >/dev/null
echo "deb https://ngrok-agent.s3.amazonaws.com buster main" | sudo tee /etc/apt/sources.list.d/ngrok.list
sudo apt update && sudo apt install ngrok

After installation, verify with ngrok version.

Step 3: Authenticate ngrok

Check if ngrok already has an auth token configured:

bash
ngrok config check

If not authenticated:

  1. Tell the user: "You need an ngrok account to create tunnels. If you don't have one, sign up at https://dashboard.ngrok.com/signup - it's free."

  2. Once they have an account, run assistant credentials prompt (via the bash tool) to securely collect their auth token. Never ask the user to paste the token directly in chat.

    bash
    assistant credentials prompt --service ngrok --field authtoken \
      --label "ngrok Auth Token" \
      --description "Get your auth token from https://dashboard.ngrok.com/get-started/your-authtoken" \
      --usage-description "ngrok authentication token for creating public tunnels"
  3. Once the credential is stored, reveal it and apply it to ngrok:

    bash
    ngrok config add-authtoken "$(assistant credentials reveal --service ngrok --field authtoken)"

    On Windows:

    powershell
    $token = assistant credentials reveal --service ngrok --field authtoken
    ngrok config add-authtoken $token

    If no value is returned, re-run assistant credentials prompt and try again.

Verify authentication succeeded by checking ngrok config check again.

Step 4: Start the Tunnel

Before starting, check for an existing ngrok process to avoid duplicates:

bash
curl -s http://127.0.0.1:4040/api/tunnels 2>/dev/null

On Windows:

powershell
Invoke-RestMethod http://127.0.0.1:4040/api/tunnels -ErrorAction SilentlyContinue

If a tunnel is already running, check whether it points to the correct local target. If so, skip to Step 5. If it points elsewhere, stop it first:

bash
pkill -f ngrok || true
sleep 1

On Windows:

powershell
Get-Process ngrok -ErrorAction SilentlyContinue | Stop-Process
Start-Sleep -Seconds 1

Start ngrok in the background tunneling to the local gateway URL:

bash
nohup ngrok http "$INTERNAL_GATEWAY_BASE_URL" --log=stdout > /tmp/ngrok.log 2>&1 &
echo $! > /tmp/ngrok.pid

On Windows:

powershell
$logPath = Join-Path $env:TEMP "ngrok.log"
$errorLogPath = Join-Path $env:TEMP "ngrok-error.log"
Start-Process ngrok -ArgumentList @("http", $env:INTERNAL_GATEWAY_BASE_URL, "--log=stdout") -RedirectStandardOutput $logPath -RedirectStandardError $errorLogPath -WindowStyle Hidden

Wait a few seconds for the tunnel to establish.

Step 4b: Verify Port Alignment

Before discovering the public URL, verify that ngrok is forwarding to the same port the gateway is actually listening on. A mismatch here causes silent failures - webhooks appear to be delivered but never reach the gateway.

Query the ngrok tunnel's target port and the gateway's configured port, then compare them:

bash
curl -s http://127.0.0.1:4040/api/tunnels | python3 -c "
import sys, json, re

data = json.load(sys.stdin)
tunnels = data.get('tunnels', [])
if not tunnels:
    print('ERROR: no active ngrok tunnel found')
    sys.exit(1)

addr = tunnels[0].get('config', {}).get('addr', '')
match = re.search(r':(\d+)$', addr)
if not match:
    print(f'ERROR: could not extract port from ngrok tunnel addr: {addr}')
    sys.exit(1)

print(match.group(1))
"
bash
echo "$INTERNAL_GATEWAY_BASE_URL" | grep -oE '[0-9]+$'

On Windows, resolve both ports without using the POSIX snippets:

powershell
$tunnel = (Invoke-RestMethod http://127.0.0.1:4040/api/tunnels).tunnels[0]
$tunnelPort = ([uri]$tunnel.config.addr).Port
$gatewayPort = ([uri]$env:INTERNAL_GATEWAY_BASE_URL).Port
@{ tunnelPort = $tunnelPort; gatewayPort = $gatewayPort }

Compare the two port numbers. If they differ, warn the user:

Port mismatch detected: ngrok is forwarding to port X but the gateway is listening on port Y. Webhooks will not reach the gateway. Stop ngrok (Step 4), then re-run this skill to start ngrok on the correct port.

If the ports match, proceed silently to Step 5.

Step 5: Discover the Public URL

Query the ngrok local API for the tunnel's public URL:

bash
curl -s http://127.0.0.1:4040/api/tunnels | python3 -c "
import sys, json
data = json.load(sys.stdin)
tunnels = data.get('tunnels', [])
for t in tunnels:
    url = t.get('public_url', '')
    if url.startswith('https://'):
        print(url)
        sys.exit(0)
for t in tunnels:
    url = t.get('public_url', '')
    if url:
        print(url)
        sys.exit(0)
print('ERROR: no tunnel found')
sys.exit(1)
"

If no tunnel is found, check /tmp/ngrok.log for errors and report them to the user.

On Windows, discover the URL and inspect the logs with:

powershell
$tunnel = (Invoke-RestMethod http://127.0.0.1:4040/api/tunnels).tunnels | Where-Object { $_.public_url -like "https://*" } | Select-Object -First 1
$tunnel.public_url
Get-Content (Join-Path $env:TEMP "ngrok.log") -ErrorAction SilentlyContinue
Get-Content (Join-Path $env:TEMP "ngrok-error.log") -ErrorAction SilentlyContinue

Step 6: Persist the Ingress Setting

Save the discovered public URL and enable ingress:

bash
assistant config set ingress.publicBaseUrl "<public-url>"
assistant config set ingress.enabled true

Verify it was saved:

bash
assistant config get ingress.publicBaseUrl
assistant config get ingress.enabled

Step 7: Report Completion

Summarize the setup:

  • Public URL: <the-url> (this is your ingress.publicBaseUrl)
  • Local gateway target: $INTERNAL_GATEWAY_BASE_URL
  • ngrok dashboard: http://127.0.0.1:4040

Provide useful follow-up commands:

  • Check tunnel status: curl -s http://127.0.0.1:4040/api/tunnels | python3 -c "import sys,json; [print(t['public_url']) for t in json.load(sys.stdin)['tunnels']]"
  • View ngrok logs: cat /tmp/ngrok.log
  • Restart tunnel: pkill -f ngrok; sleep 1; nohup ngrok http "$INTERNAL_GATEWAY_BASE_URL" --log=stdout > /tmp/ngrok.log 2>&1 &
  • Stop tunnel: pkill -f ngrok
  • Rotate URL: Stop and restart ngrok (free tier assigns a new URL each time; update ingress.publicBaseUrl afterward)

Important: On ngrok's free tier, the public URL changes every time the tunnel restarts. After restarting, re-run this skill or manually update ingress.publicBaseUrl and any registered webhooks (e.g., Telegram).

Troubleshooting

ngrok not installed

Run the install commands in Step 2. On macOS, make sure Homebrew is installed first (brew --version).

Auth token invalid or expired

Sign in to https://dashboard.ngrok.com, copy a fresh token from the "Your Authtoken" page, and re-run Step 3.

ngrok API (port 4040) not responding

The ngrok process may not be running. On macOS or Linux, check with ps aux | grep ngrok. On Windows, use Get-Process ngrok -ErrorAction SilentlyContinue. If it is not running, start it per Step 4. If it is running but port 4040 is unresponsive, check /tmp/ngrok.log ($env:TEMP\ngrok.log on Windows) for errors.

Gateway not reachable on local target

Re-check the local gateway target with echo $INTERNAL_GATEWAY_BASE_URL. Run curl -s "$INTERNAL_GATEWAY_BASE_URL/healthz" to verify it is reachable. If the gateway is not running, start the assistant first.

On Windows, use $env:INTERNAL_GATEWAY_BASE_URL and Invoke-RestMethod "$env:INTERNAL_GATEWAY_BASE_URL/healthz".

"Too many connections" or tunnel limit errors

ngrok's free tier allows one tunnel at a time. Stop any other ngrok tunnels before starting a new one.

ngrok port doesn't match gateway port

Symptom: Webhooks return connection refused or timeouts even though both ngrok and the gateway appear to be running.

Cause: ngrok is forwarding to a different port than the gateway is listening on. This can happen if the gateway port was changed after ngrok was started, or if ngrok was started manually with a hardcoded port.

Fix: Stop ngrok (Step 4), verify the gateway URL with echo $INTERNAL_GATEWAY_BASE_URL, then re-run this skill to start ngrok on the correct port.

ngrok automatically restarts with wrong port

On macOS, if the ngrok process automatically re-spawns on the incorrect port, check for a launch agent at ~/Library/LaunchAgents/com.ngrok.tunnel.plist. If it exists, remove or update it.

Frequently asked questions

What does the Public Ingress AI skill do?

Set up and manage ngrok-based public ingress for local assistants; do not use this in managed mode when platform callback routing is available

Why use Public Ingress on TypingMind?

Because you install it once and use it with any model. Public Ingress is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Public Ingress in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/vellum-ai/vellum-assistant/tree/main/skills/public-ingress. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Public Ingress?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Public Ingress?

As many as you like. As long as a model supports skills, you can use Public Ingress with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Public Ingress AI skill free?

Yes. It is published on GitHub by vellum-ai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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