NETSCOUT SYSTEMS, INC. today announced Model Context Protocol (MCP) connectivity for its Omnis™ AI Insights solution. This update enables AI assistants and agents to access real-time network data, known as Smart Data, on demand, providing them with trusted operational evidence for more accurate decision-making.
The Omnis AI Insights solution is built upon NETSCOUT’s Data Platform, utilizing its Adaptive Service Intelligence (ASI) technology. This technology processes detailed data at the source, creating compact, AI-ready Smart Data for downstream systems, ensuring a richer and more scalable source of contextual network intelligence.
Functionality Overview
Two core components drive this process: the Omnis Sensor and the Omnis Streamer. The Omnis Sensor captures semantic data at critical network points, gathering application, service, transaction, and behavioral context in real time. This generates metadata that retains operational meaning at the point of observation, providing high-fidelity evidence for AI models.
The Omnis Streamer gathers and refines this AI-ready Smart Data, customizing it for specific domains or use cases through customizable playbooks. It delivers datasets through platform integrations with tools like Splunk, ELK Stack, Datadog, ServiceNow, and Dynatrace, or directly to AI assistants and agents via its integrated MCP server.
Advantages of Smart Data
By enhancing network data before it reaches AI models, NETSCOUT minimizes the volume, cost, and complexity of processing raw telemetry. This provides AIOps (Artificial Intelligence for IT Operations), observability, security, and analytics systems with more actionable information, enabling quicker and more dependable decisions. The result is a ground truth, evidence-based view of operations essential for reliable autonomous action by AI agents.
For organizations, MCP connectivity ensures AI assistants and models have access to pertinent Smart Data during runtime, guided by NETSCOUT-provided tools. This helps IT professionals integrate AI-ready Smart Data into analytics and AI platforms more effectively, addressing issues like hallucinations and high costs.
Practical Implementation
In a live deployment, NETSCOUT’s Smart Data demonstrated its value by preserving critical network details such as minimum window size, total retransmit count, and zero-window event count, even when traditional monitoring tools showed no application errors. This allowed AI to verify facts rather than infer reality, resulting in more accurate answers and reduced costs.
Phil Gray, AVP of product management at NETSCOUT, emphasized the importance of reliable conclusions. “By adding MCP tools alongside our existing Kafka streaming capabilities, Omnis AI Insights gives IT professionals the flexibility to feed AI-ready Smart Data into analytics and AI platforms at scale and cost-effectively,” he stated. This approach helps organizations power AI with a compact, curated, trusted source of network truth.
These new features enhance the value of existing NETSCOUT investments and provide a distinct data foundation for future AI innovation. They put trusted operational context to work across AI, analytics, observability, service assurance, security, and data lake environments. Additionally, Omnis Sensor Adaptors ensure customers can add these capabilities to their existing NETSCOUT infrastructure, protecting their investments.
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