Mealissa is a secure, OpenAI- and Anthropic-compatible gateway that gives self-hosted local LLMs a globally accessible API endpoint, with prompts encrypted in transit and never stored. This page compares it with the most common alternatives for reaching a local model remotely: general-purpose tunnels (ngrok), private VPN meshes (Tailscale), and hosted cloud LLM APIs. Each tool is excellent at what it was built for — the difference is what that is.
| Mealissa | ngrok | Tailscale | Cloud LLM APIs | |
|---|---|---|---|---|
| Built for | Exposing self-hosted LLMs as a secure API | Tunneling any local port to a public URL | A private network between your own devices | Hosted frontier models as a service |
| LLM API endpoint | OpenAI- and Anthropic-compatible endpoints out of the box | Whatever your local server exposes | Whatever your local server exposes | The provider's own API |
| Authentication | License-key auth built in; keys managed from a dashboard | You configure it yourself — a tunneled Ollama has no auth by default | Limited to devices enrolled in your tailnet | Provider API keys |
| Works behind NAT | Yes — the agent connects outbound, no port forwarding | Yes | Yes | Not applicable |
| Multiple machines | Group nodes behind one endpoint; requests dispatched to a connected node | One tunnel per service | Every device joins the mesh, but no API-level routing | Not applicable |
| Prompt handling | Encrypted in transit, never stored | Traffic passes through ngrok's edge servers | Peer-to-peer within your tailnet | Processed on provider infrastructure, retention per provider policy |
| Models | Any model in the Ollama library, on your hardware | Yours | Yours | The provider's models only |
| Cost model | Free Pico plan; flat paid plans by model parameter size | Free and paid tiers per tunnel features | Free for personal use; paid per user | Pay per token |
ngrok is a general-purpose tunnel: it forwards a public URL to any port on your machine, and it does that very well. Point it at Ollama, though, and what outside callers reach is your raw Ollama server — which ships with no authentication. API keys, per-caller limits, and usage visibility all become things you assemble and maintain yourself.
Mealissa is purpose-built for exactly this case. The mealissa-llm-agent connects outbound from your machine, so nothing on your network is opened to the public internet. The endpoint you share speaks the OpenAI and Anthropic APIs, authentication is a revocable license key, and several machines can serve one endpoint as a group — requests are dispatched to whichever node is connected.
Choose ngrok when you are exposing web apps, webhooks, or anything that is not an LLM, or when you want to own the entire auth stack yourself.
Tailscale builds a private WireGuard mesh between devices you enroll, and it is the right answer when the only callers are you and machines you control. But every caller must join your tailnet: giving a deployed app, a teammate, or a third-party tool access to your model means enrolling their machine — and even then there is no API-key layer and no LLM-format endpoint, just network reachability to a raw Ollama port.
Mealissa gives your local model a public HTTPS endpoint with license-key authentication. Callers install nothing and join nothing — any code that can call the OpenAI or Anthropic API can call your model, from anywhere, with a key you can revoke at any time.
Choose Tailscale when you want private access among your own devices and never need to hand an API endpoint to anyone outside your network.
Cloud LLM APIs offer frontier-model quality with zero infrastructure — but your prompts are processed on the provider's servers under the provider's retention policy, and you pay for every token. Mealissa keeps inference on hardware you own: any model from the Ollama library runs locally, the gateway relays prompts encrypted in transit and never stores them, and pricing is a flat license by model parameter size rather than per-token metering.
Because Mealissa's endpoints are OpenAI- and Anthropic-compatible, code written against a cloud API switches to your local model by changing only the base URL and the key — the SDKs stay the same.
Choose a cloud LLM API when you need frontier-model capability beyond what your local hardware can run, or you do not want to operate any machine at all.
Install Ollama, pull a model, download the agent for Windows or Linux, and register your node — the install guide walks through every step. A free Pico plan and a 7-day trial are available from the dashboard.