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NETSCOUT Adds MCP Connectivity to Omnis AI Insights for AI-Ready Network Intelligence

NETSCOUT

NETSCOUT has announced Model Context Protocol (MCP) connectivity for its Omnis™ AI Insights solution. The new capability gives AI assistants and agents on-demand access to AI-ready Smart Data, NETSCOUT’s real-time operational evidence, providing the trusted context they need to support more accurate and informed decisions.

AI-ready Smart Data builds on NETSCOUT’s patented Adaptive Service Intelligence™ (ASI) technology, using granular data to provide a richer, more scalable source of contextual network intelligence. NETSCOUT performs early semantic extraction and context optimisation at source, transforming ASI data into compact, AI-ready Smart Data before it enters downstream systems. Omnis Sensor and Omnis Streamer are key components of NETSCOUT’s Omnis AI Insights solution, moving intelligence closer to the source of the data and enabling network infrastructure to evolve from simply producing telemetry to delivering contextual, AI-ready network intelligence.

Enriching network data before it reaches an AI model reduces the volume, cost, and complexity of processing raw telemetry while giving AIOps, observability, security, and analytics systems more meaningful evidence for faster, more reliable decisions and increasingly autonomous operations.

Extending the Value of the NETSCOUT Data Platform

Omnis AI Insights provides organisations with a ground truth, evidentiary view of operations that AI agents and assistants require for trusted autonomous action:

AI-Ready Datasets: Clean Inputs, Confident Answers

“Everyone knows there is no value to conclusions that cannot be trusted,” said Phil Gray, AVP, product management, NETSCOUT. “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, while also making that same context-rich intelligence directly accessible to Models and Agents. This helps organisations power AI with a compact, curated, trusted source of network truth rather than fragmented operational signals that suffer from hallucinations and high token spends.”

In a live NETSCOUT deployment, conventional application monitoring tools indicated no application errors and nothing to investigate, while underlying network conditions degraded the user experience. NETSCOUT Smart Data preserved exactly what happened across the network, including the minimum window size, total retransmit count, and zero-window event count, allowing AI to verify facts rather than infer reality.

NETSCOUT AI-ready Smart Data helps customers reach accurate answers faster, reduce token and infrastructure costs, and advance toward governed autonomous operations with greater confidence. It also extends the value of existing NETSCOUT investments while providing a differentiated data foundation for future AI innovation. These new capabilities in the Omnis AI Insights solution put trusted operational context to work across AI, analytics, observability, service assurance, security, and data lake environments without re-platforming or building new data pipelines.

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Also Read: NETSCOUT Enhances DDoS Protection to Defend Applications Against CDN-Burning Attacks

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