Liongard Adds MCP, Natural-Language Query, Reporting Integrations To Boost MSP Automation

‘At the end of the day, what we’ve been doing as humans is gathering data, exporting spreadsheets and cross-referencing everything. And by the time we’re done, we didn’t even get to the insight. What we’re trying to do is connect that data directly to the outcome,’ says Joe Alapat, Liongard founder and chief strategy officer.

Liongard is expanding its push to become the system of authority for MSPs, rolling out a series of updates to give MSPs a reliable, real-time foundation of asset intelligence that can power automation and AI.

The Houston-based vendor Thursday unveiled new capabilities within LiongardIQ, including Model Context Protocol (MCP) server availability, natural language querying through its AI-powered Roar Assistant, enhanced network discovery and expanded reporting integrations. Together, the updates address MSPs trying to layer AI and automation on top of incomplete or outdated data.

“Without that trusted foundation, everything kind of falls apart,” Liongard founder and chief strategy officer Joe Alapat told CRN in an interview. “Automation starts running on assumptions, AI is querying stale data, and then you’re making decisions that just aren’t grounded in reality.”

[Related: Liongard CEO: ‘LiongardIQ Closes Doors Before The Attacker Even Knocks’]

For MSPs, that challenge is becoming more urgent as they juggle increasingly complex environments across customers, tools and security layers, he added. Liongard’s approach focuses on turning that data into something actionable.

“At the end of the day, what we’ve been doing as humans is gathering data, exporting spreadsheets and cross-referencing everything,” he said. “And by the time we’re done, we didn’t even get to the insight. What we’re trying to do is connect that data directly to the outcome.”

The announcements also reflect a broader shift in how MSPs operate as they move deeper into AI-driven services. According to Alapat, much of the market is still in an experimental phase.

“We’re in that stage where people see what’s possible, and they’re trying things out,” he said. “But then the question becomes, how does the organization move forward? How do you operationalize it?”

Inconsistent, outdated or incomplete information can quickly derail both automation and customer trust. Without accurate data, MSPs risk recommending fixes for issues that have already been resolved or systems that have already been upgraded, he added.

And that problem becomes more pronounced as MSPs scale.

“You’ve got account managers juggling 20 customers, switching context all day,” he said. “They need the system to give them that context instantly.”

That opportunity can be significant MSPs, he said, but it starts internally.

“If you’re trying to transform your customers with AI, you’ve got to start with your own operations,” he said. “You’ve got to use it, understand it and build on a foundation that’s actually trustworthy.”

Brian Bode echoed Alapat’s sentiment in that the MSPs succeeding “aren’t the ones with the most sophisticated tools.”

“They’re the ones who solved the data problem first,” Bode, director of managed services platforms and automation at South Bend, Indiana-based Aunalytics, said in a statement to CRN. “You can’t build an AI-driven operation on a foundation you don’t trust. Liongard gives us data about our tools we can trust.”