Stop reading dashboards. Start asking questions.

Unified endpoint telemetry for your entire fleet — Windows, macOS, Linux, Raspberry Pi, NVIDIA Jetson, QNAP NAS, and Synology NAS — with a native MCP server your AI agent connects to directly. No dashboard required. Free for up to 3 devices.

Endpoint Performance Monitoring for Your Entire Fleet

From developer workstations to network-attached storage, ML-EPM gives you unified visibility across every device in your organization — without compromise.

One agent. Every platform.

Windows 10 & 11 — lightweight background service with a system tray interface; auto-updates silently in the background
macOS — native daemon and menu bar app, Apple Silicon and Intel, notarized and ready for your MDM
Linux — zero-dependency Go binary for servers, Raspberry Pi, and embedded ARM devices running Ubuntu, Debian, and more
QNAP NAS — persistent across QTS firmware updates, purpose-built for QTS's init model
Synology NAS — supports DiskStation Manager 7, reports alongside the rest of your fleet

Know what's happening, everywhere.

ML-EPM collects CPU, memory, disk, battery, WiFi signal, network connectivity, OS patch state, SMART drive health, service watchdog status, and security posture — all in one place. Agents self-update, re-enroll seamlessly after hardware refreshes, and report every five minutes to your cloud dashboard. Built for IT teams that manage a mix of workstations, servers, and appliances — not just the obvious ones.

What ML-EPM Does

Fleet Intelligence

Traditional monitoring gives you data. ML-EPM gives you answers. Because all telemetry flows through an MCP server, your AI agent can reason across your entire fleet — correlating signals, spotting patterns, and surfacing what actually matters.

The intelligence lives in the agent, not in a fixed set of dashboard widgets. That means you're not limited to the questions someone pre-built a chart for — you can ask anything.

  • "Which machines haven't reported in 24 hours?"
  • "Are any devices running an OS version with known vulnerabilities?"
  • "Which machines are low on disk and also haven't been patched recently?"
  • "Summarize the health of my fleet in plain English."
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Intelligent Monitoring

Because ML-EPM exposes your fleet through a standard MCP server, any MCP-compatible AI agent can query it — not just interactively, but autonomously. The intelligence layer is entirely yours to define.

For example — connect an open-source AI model to ML-EPM's MCP server and build a fully autonomous daily fleet report and have the model investigate the fleet on its own: checking for security issues, aging software, and unhealthy devices, then write a plain-English summary that is emailed to the team.

That's the shift ML-EPM enables: from a dashboard you check, to an agent that works for you, intelligently, behind the scenes.

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Heterogeneous Fleet Support

One agent. Every machine. ML-EPM runs on all the platforms your fleet actually uses — not just the ones a traditional monitoring vendor supports.

  • Windows 10 & 11 — lightweight background service with system tray interface; auto-updates silently
  • macOS — native daemon and menu bar app, Apple Silicon and Intel, notarized and MDM-ready
  • Linux — zero-dependency Go binary for servers, Raspberry Pi, and embedded ARM devices
  • QNAP NAS — persistent across QTS firmware updates, purpose-built for QTS's init model
  • Synology NAS — supports DiskStation Manager 7, reports alongside the rest of your fleet
Windows 10 & 11 macOS (Apple Silicon & Intel) Linux x86 Linux ARM Raspberry Pi NVIDIA Jetson QNAP NAS Synology NAS
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Security and Health Posture

Every enrolled device reports a complete security and health snapshot in a single telemetry stream — no separate tools required.

Covers: patch compliance, disk encryption, firewall state, screen lock, SMART disk health, and service monitoring.

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AI-Native Architecture

ML-EPM ships with a native MCP server from day one. It integrates with Claude and any MCP-compatible AI agent out of the box.

That means your AI agent can query your fleet directly — no MCP glue required.

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ML-EPM vs. Traditional Monitoring

See how ML-EPM compares to tools like Datadog, Zabbix, and Nagios.

Dimension Traditional Tools (Datadog, Zabbix, Nagios) ML-EPM
Interface Dashboard — you read charts Natural language — you ask questions
Insight delivery You interpret the data Your AI agent interprets the data
Setup complexity Configure thresholds, alert rules, dashboards Install agent, connect MCP server
Mixed fleet support Platform-specific agents or limited coverage Single agent: Windows, macOS, Linux x86/ARM, QNAP NAS, Synology NAS, Jetson, Raspberry Pi
AI integration Third-party add-on or none MCP-native from day one
False positive handling Alert storms requiring manual triage Platform-aware interpretation (e.g., MacBook lid-close ≠ outage)
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Frequently Asked Questions

No. ML-EPM works with any MCP-compatible AI agent — Claude is one supported option, but not the only one. The ML-EPM MCP server exposes your fleet telemetry as a standard MCP data source, so any agent that supports MCP can query it. Claude (via Claude Desktop or the API) is the most commonly used option today.

Any AI agent or tool that supports the Model Context Protocol (MCP) can connect to ML-EPM. This includes Claude Desktop, custom agents built with the Anthropic SDK, and any other MCP-compatible client. As the MCP ecosystem grows, ML-EPM will work with new agents without requiring changes to the server.

Yes — telemetry data is transmitted from your enrolled devices to the ML-EPM cloud backend (hosted on AWS), where it is stored and made available to the MCP server. Data is encrypted in transit and at rest. Your AI agent queries the ML-EPM MCP server, which retrieves data from the cloud backend. If you have specific data residency or compliance requirements, contact us to discuss the Enterprise self-hosted option.

Traditional monitoring tools like Datadog, Zabbix, and Nagios are built around dashboards: you configure alert thresholds, watch charts, and interpret the data yourself. ML-EPM is built for AI agents: instead of reading a dashboard, you ask your AI agent a question and it interprets the telemetry for you.

ML-EPM also covers platforms that traditional tools handle poorly — QNAP NAS, Synology NAS, NVIDIA Jetson edge devices, and Raspberry Pi — with a single unified agent. And because the MCP server is native from day one, there's no third-party integration layer to maintain.

Simple, Transparent Pricing

Start free. Upgrade when you need more seats or features.

Free

$0/mo
Up to 3 devices
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Home

$5/mo
Up to 10 devices
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Business

$99/mo
Up to 250 devices
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Enterprise

$299/mo
Up to 1,000 devices
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Annual plans save approximately 17% compared to monthly billing. Need more than 1,000 seats? Contact sales for custom pricing.

Get started before launch pricing changes.

ML-EPM is available now. Request early access to lock in launch pricing and start monitoring your fleet.