Omnis AI Insights adds MCP connectivity, giving AI assistants and agents on-demand access to curated network evidence for faster, more reliable decisions.
NETSCOUT is extending its Omnis AI Insights solution with Model Context Protocol (MCP) connectivity, allowing AI assistants and agents to access its AI-ready Smart Data directly at runtime.
The move addresses a growing challenge in enterprise AI: models can only make reliable operational decisions when they have access to accurate, contextual and trusted data. NETSCOUT’s Smart Data is derived from its Adaptive Service Intelligence (ASI) technology, with semantic extraction and context optimisation performed close to the source.
Omnis Sensor captures application, service, transaction and behavioural context in real time, while Omnis Streamer curates the resulting Smart Data for downstream platforms and now AI assistants through its built-in MCP server.
“Everyone knows there is no value to conclusions that cannot be trusted. 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.” — Phil Gray, AVP, Product Management, NETSCOUT
For IT and security teams, the approach reduces the need to push large volumes of raw network telemetry into AI systems. By providing compact, context-rich evidence, organisations can reduce processing complexity and token consumption while giving AI models stronger operational context.
NETSCOUT says the capability can support AIOps, observability, security, service assurance and analytics, while integrating with platforms including Splunk, ELK Stack, Datadog, ServiceNow and Dynatrace.
The significance extends beyond another AI integration. As enterprises move toward increasingly autonomous operations, the quality and provenance of the data feeding AI agents becomes critical. NETSCOUT is positioning its network evidence as a trusted foundation that can help AI systems verify operational reality rather than infer it from fragmented telemetry.
