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Ac Infinity MCP

by ober37

Monitor AC Infinity controllers, inspect grow data, and manage port automations through MCP-compatible assistants.

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Install Ac Infinity MCP

Pick your client, then add it in one click or paste the config.

STDIOPython
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "ober37-ac-infinity-mcp": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/ober37/ac-infinity-mcp.git",
        "ac-infinity-mcp"
      ],
      "env": {
        "AC_INFINITY_EMAIL": "YOUR_VALUE_HERE",
        "AC_INFINITY_PASSWORD": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

Install not yet sandbox-tested— we haven't run this command through our automated sandbox yet. Not a red flag; we're working through the catalog.

Overview

ober37/ac-infinity-mcp MCP server connects MCP-compatible AI assistants to AC Infinity cloud controllers. It provides tools for live and historical readings, VPD and environmental analytics, port control, grow-stage templates, and Advance Automation programs. Write operations use dry-run mode by default, while reads can inspect controller state and trends. Use it when you want conversational monitoring or controlled automation of supported AC Infinity grow hardware.

Use cases

  • Discover AC Infinity controllers and ports
  • Inspect live and historical grow-environment readings
  • Analyze VPD drift and environmental trends
  • Set port speeds or operating modes with dry runs
  • Manage grow-stage and Advance Automation programs

Key features

  • Live temperature, humidity, VPD, and port readings
  • Historical time-series data with optional bucketing
  • VPD, temperature, and humidity automation
  • Port speed, power, mode, and status controls
  • Grow-stage templates and Advance Automation management
  • Built-in prompts for troubleshooting and setup

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 1d ago

Recent health check succeeded.

7/7 checks healthy over the last 84d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 13d ago via OSV.dev · ac-infinity-mcp (PyPI)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars9Stargazers on the source repository.
Last commit10d agoMost recent push to the default branch.
Directory activity4 viewsConfig copies, upvotes, and views on AllMCPs.

How Ac Infinity MCP works

What ober37/ac-infinity-mcp MCP server does

ober37/ac-infinity-mcp MCP server exposes AC Infinity controller data and controls through the Model Context Protocol. It connects to the AC Infinity cloud API, allowing an MCP client to discover devices, inspect sensor readings, review port state, and request controller changes without using the AC Infinity mobile application directly.

Supported hardware listed by the project includes the UIS Controller 69 Pro, UIS Controller 69 Pro+, and UIS Controller 89 AI+. The 69 Pro models support reads and writes through the legacy protocol. The 89 AI+ supports readings and per-port writes, with protocol-specific requirements described in the project documentation.

How it works

The server runs as a Python application built with FastMCP and communicates with AC Infinity using account credentials supplied at runtime. An MCP client starts the server over stdio and presents its tools and prompts to the assistant. The assistant can then call read-only operations for current or historical data, or prepare and execute device changes.

Write tools default to dry_run=True. In that mode, the server returns the payload it would send instead of changing equipment. A caller must explicitly use dry_run=False to perform a write. This applies to port controls, automation settings, grow-stage templates, and Advance Automation operations.

Three prompts are also registered: one for VPD troubleshooting, one for setting up a new grow, and one for interpreting environment alerts and health grades.

Setup and configuration

Install with pip from the Git repository, create an isolated virtual environment, or run the executable with uvx. Python 3.11 or later is required. The package provides an ac-infinity-mcp executable for MCP client configuration.

Set these required environment variables:

  • AC_INFINITY_EMAIL: AC Infinity account email
  • AC_INFINITY_PASSWORD: AC Infinity account password

Claude Desktop, Cursor, and Windsurf examples in the project use a stdio command configuration with these variables in the client environment. Docker Compose is also documented; the container runs over stdio and can be connected through a stdio bridge such as mcp-proxy.

Tools and capabilities

The ober37/ac-infinity-mcp MCP server includes discovery, readings, analytics, port status, write, automation, grow-stage, and Advance Automation tools. Read operations include device discovery, current temperature, humidity, VPD, port states, historical time-series data, port settings, and port activity reports.

Analytics tools can check VPD drift for a grow stage, calculate an environmental health score from 0 to 100 with an A–F grade, and identify linear trends with a seven-day projection. Port controls can set speed from 1 to 10, turn ports on or off, switch modes, and configure temperature, humidity, or VPD automation.

Advance Automation tools can list, inspect, create, enable, disable, update, and delete named programs. They can also add or remove individual rules. Grow-stage templates apply combined VPD, temperature, and humidity automation, while the breakout operation returns a safe way to remove a port from automation control.

Limitations and notes

AI+ controller support is not uniform across every automation feature. Reads and some in-place Advance Automation edits are documented as verified, while creation, enable/disable behavior, and other operations have limited or hardware-specific verification. apply_grow_stage_template and break_out_of_automation are held back on AI+ pending hardware verification and refuse to write there.

The project notes that per-port writes on the 89 AI+ require a minversion header. The upstream AC Infinity cloud API does not support HTTPS, so deployment should account for that transport limitation when handling account credentials and network traffic.

Read the full README View source on GitHub

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Frequently Asked Questions about Ac Infinity MCP

ober37/ac-infinity-mcp is an MCP server that connects AI assistants to AC Infinity cloud controllers, exposing tools for device discovery, live and historical readings, analytics, port control, sensor-based automation, grow-stage templates, and Advance Automation programs. It communicates through the AC Infinity cloud API and supports compatible MCP clients.

Install it from the Git repository with pip, run it in a Python 3.11+ virtual environment, or use `uvx --from git+https://github.com/ober37/ac-infinity-mcp.git ac-infinity-mcp`. Docker Compose is also documented and runs the server over stdio.

It requires `AC_INFINITY_EMAIL` and `AC_INFINITY_PASSWORD`. Provide the AC Infinity account email and password in the MCP client's environment configuration or through the documented Docker `.env` file.

Yes, Cursor is documented as a compatible client. Configure its MCP settings with the path to the `ac-infinity-mcp` executable and provide the required AC Infinity credentials as environment variables.

Write operations default to dry-run mode, so they return the payload that would be sent without changing equipment. Pass `dry_run=False` only when you want to execute the requested port or automation change.

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