AI Integration · Native MCP Server

Talk to your infrastructure. It listens — and acts.

Widgelix connects your devices to AI assistants like ChatGPT and Claude. Ask in plain language to build a dashboard, set an alert, or check what's happening in a building — and the AI does it. No console to master, no documentation to read.

Book a Demo How it works →

Works with any MCP-compatible AI assistantPermission-controlledFully audited

Widgelix · AI Assistantlive

Alert me if any freezer goes above −15°C for 5 minutes, and shut its load down.

On it — building the rule now

Rule created · Freezer over-temp

WHENtemp > −15°Cfor5 min

THENDownlink · shut loadSlack alert

Armed · monitoring 24 freezersaudit

/ The idea

Most IoT platforms make you learn them.
This one you just talk to.

Every IoT platform has a learning curve — menus, schemas, rule builders, decoder formats. Widgelix removes it. Because it exposes the whole platform through a native MCP server — the open standard that lets AI assistants connect to real systems — a connected AI can both run your infrastructure and set it up for you, from a plain-language request. You bring the intent. The AI handles the mechanics.

/ Capabilities

Two things your AI can do with Widgelix

Configure, by conversation

Set up the platform without touching the console. Describe what you want, and the AI builds it: device types and decoders, dashboards, and automation rules — all from natural language.

Example

“Connect this air-quality sensor, show CO₂ and temperature on a dashboard, and alert me if CO₂ stays over 1000 ppm for 15 minutes.”

The AI creates the decoder, builds the dashboard, and writes the rule. Ready in minutes.

Operate, in real time

Once it's running, the AI becomes an operator. It reads live and historical telemetry across every device, interprets what's happening, and takes action — within the permissions you set.

Example

“Which sites had abnormal energy use this week, and shut down the overnight load on the worst one.”

The AI analyzes the data, names the site, and sends the downlink command — with a logged audit trail.

/ How agents work

Read. Reason. Act.

Read

Agents access real-time and historical data across all your connected devices.

Reason

Agents interpret conditions, spot anomalies, and decide what needs to happen.

Act

Agents trigger rules and send downlink commands to devices — strictly within the limits you define.

/ Architecture

Built on MCP, the open standard for AI-to-system connections

Widgelix ships with a native Model Context Protocol (MCP) server. MCP is the open standard that lets AI assistants securely connect to external systems and act on them. Any MCP-compatible client — ChatGPT, Claude, or your own agent — connects directly to your Widgelix environment and gains structured access to your devices, dashboards, and rules.

There's no middleware to build and no custom integration per assistant. Connect the MCP server once, and your infrastructure becomes something an AI can read and operate through a single, standard interface.

Open standard

MCP-compatible by design; not locked to one AI vendor.

Structured access

Agents see devices, telemetry, dashboards, and rules as first-class objects, not scraped text.

Two-way

Agents don't just read; they can send downlink commands and build configuration.

/ Trust

You stay in control. Always.

Letting an AI act on physical infrastructure only works if the guardrails are real. They are.

Role-based permissions

Every agent operates inside the exact scope you grant. No access you didn't give.

Full audit trail

Every read and every action an agent takes is logged, attributable, and reviewable.

Bounded actions

Agents can only trigger what your rules and permissions allow — not arbitrary commands.

Human-in-the-loop, when you want it

Keep sensitive actions gated behind approval.

/ In practice

What teams actually do with it

Facility managers

Ask plain-language questions across a whole portfolio ("which buildings are coldest right now?") instead of clicking through dashboards.

System integrators

Stand up a new client's devices, dashboards, and alerts by describing them, cutting setup time per project.

Operations teams

Let an agent watch telemetry around the clock and act on anomalies the moment they cross a threshold.

Developers

Connect a custom agent to the MCP server and build automation on top of structured, permissioned access.

See your infrastructure answer back.

Bring a device and a question. We'll show you how Widgelix lets an AI assistant set it up, read it, and act on it — live, in a 30-minute walkthrough.

Live demo with ChatGPT or Claude connected to real devices
A look at the permission and audit model
Setup-by-conversation, end to end

/ FAQ

Frequently asked

+What is MCP?

The Model Context Protocol — an open standard that lets AI assistants connect to and act on external systems. Widgelix includes a native MCP server, so any MCP-compatible AI can work with your infrastructure.

+Which AI assistants work with it?

Any MCP-compatible client, including ChatGPT and Claude, as well as custom agents you build yourself.

+Can the AI actually control devices, or only read data?

Both — within your permissions. Agents read telemetry and can send downlink commands to actuate devices, always inside the scope and audit controls you define.

+Is it safe to let an AI act on my infrastructure?

Every agent action is permission-scoped and logged. Agents can only do what your roles and rules allow, and you can keep sensitive actions behind human approval.

+Do I need to write code?

No. Configuration and operation happen through natural-language requests to a connected assistant. Developers can build directly against the MCP server if they want deeper automation.