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BlueCat Announces Tech Preview of MCP Servers and Expansion of LiveAssist

BlueCat Networks announced new portfolio innovations designed to enable agentic AI in network operations, including a tech preview of its MCP Servers and the expansion of LiveAssist, its virtual engineer, across the BlueCat platform.

BlueCat unifes network identity, policy, and telemetry into a unified data foundation. This approach allows agentic AI systems to understand context and take coordinated action across the network.

“We unify multi-vendor network data and give customers control over how and where AI runs, whether that’s multiple deployment models, AI agents, or LLMs,” said Scott Fulton, Chief Product & Technology Officer at BlueCat. “Our Intelligent NetOps foundation lets them put AI into production and see real returns, without putting network reliability and performance at risk.”

To extend this foundation throughout the broader AI ecosystem, BlueCat is launching a tech preview of its MCP Servers, which connect BlueCat’s network data and capabilities to a growing range of AI agents and platforms.

These integrations provide secure, structured access to real-time and historical network context, allowing AI tools to query, analyze, and act on network intelligence across integrated development environments, chat interfaces, and enterprise workflows. MCP Servers also include pre-built tools that help NetOps teams accelerate workflow development and improve the efficiency of LLM-driven operations.

BlueCat is also expanding LiveAssist, its virtual engineer, across its entire product portfolio, documentation, and support knowledge base.

LiveAssist uses BlueCat’s unified data foundation to move beyond basic queries. It helps teams investigate issues, understand root cause, and act through a single, conversational workflow. By combining real-time and historical network telemetry with configuration, DDI, and identity data, LiveAssist ensures a seamless progression from question to insight to execution.

“In complex environments, resilience and clarity aren’t optional. BlueCat delivers both,” said Mark Taylor, Enterprise Team Lead (Finance) at Techary, a UK-based technology services partner that delivers end-to-end IT services. “Its flexible architecture and transparent pricing remove friction, and its unified data layer is what allows AI-driven systems to operate with real precision instead of guesswork.”

MCP Servers integrated with LiveAssist are in tech preview across the BlueCat portfolio. In July, MCP Servers will start to become available via a public registry and included with base product licenses for use with other agentic platforms.

LiveAssist, which is generally available with BlueCat's network observability products, will extend to DDI - starting in July - and run on the BlueCat Horizon SaaS platform.

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BlueCat Announces Tech Preview of MCP Servers and Expansion of LiveAssist

BlueCat Networks announced new portfolio innovations designed to enable agentic AI in network operations, including a tech preview of its MCP Servers and the expansion of LiveAssist, its virtual engineer, across the BlueCat platform.

BlueCat unifes network identity, policy, and telemetry into a unified data foundation. This approach allows agentic AI systems to understand context and take coordinated action across the network.

“We unify multi-vendor network data and give customers control over how and where AI runs, whether that’s multiple deployment models, AI agents, or LLMs,” said Scott Fulton, Chief Product & Technology Officer at BlueCat. “Our Intelligent NetOps foundation lets them put AI into production and see real returns, without putting network reliability and performance at risk.”

To extend this foundation throughout the broader AI ecosystem, BlueCat is launching a tech preview of its MCP Servers, which connect BlueCat’s network data and capabilities to a growing range of AI agents and platforms.

These integrations provide secure, structured access to real-time and historical network context, allowing AI tools to query, analyze, and act on network intelligence across integrated development environments, chat interfaces, and enterprise workflows. MCP Servers also include pre-built tools that help NetOps teams accelerate workflow development and improve the efficiency of LLM-driven operations.

BlueCat is also expanding LiveAssist, its virtual engineer, across its entire product portfolio, documentation, and support knowledge base.

LiveAssist uses BlueCat’s unified data foundation to move beyond basic queries. It helps teams investigate issues, understand root cause, and act through a single, conversational workflow. By combining real-time and historical network telemetry with configuration, DDI, and identity data, LiveAssist ensures a seamless progression from question to insight to execution.

“In complex environments, resilience and clarity aren’t optional. BlueCat delivers both,” said Mark Taylor, Enterprise Team Lead (Finance) at Techary, a UK-based technology services partner that delivers end-to-end IT services. “Its flexible architecture and transparent pricing remove friction, and its unified data layer is what allows AI-driven systems to operate with real precision instead of guesswork.”

MCP Servers integrated with LiveAssist are in tech preview across the BlueCat portfolio. In July, MCP Servers will start to become available via a public registry and included with base product licenses for use with other agentic platforms.

LiveAssist, which is generally available with BlueCat's network observability products, will extend to DDI - starting in July - and run on the BlueCat Horizon SaaS platform.

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Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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