"For years, AI was primarily a chat interface. But since the launch of ChatGPT, the industry is rapidly moving towards AI that served as an analyst offering insights, to agentic AI-autonomous systems that can not only understand your operational data but also act on it. This shift presents an opportunity: how do you safely and reliably connect your most critical business workflows and data powerful, observability focused AI tools ?"
"The Model Context Protocol (MCP) is an open standard that creates a unified, bi-directional channel between large language models (LLMs) and external tools. (To learn more about the protocol, check out our previous post on Introducing MCP Support). Before MCP, connecting AI agents to a business tool (like Salesforce, a SQL database, or a proprietary API) required a custom, one-off integration that had to rebuild that integration from scratch."
"The New Relic AI MCP Server opens up a standardized way of enabling a powerful ecosystem of agents that fuel advanced agentic workflows. This allows New Relic to bring intelligent insights to any external MCP-compliant AI agent, eliminating the need for custom, brittle, one-off integrations. The MCP Server now provides actionable observability data where users work: Seamless Ecosystem Integration: This integration allows popular AI assistants like GitHub Copilot, ChatGPT, Claude, and Cursor to access detailed New Relic observability data directly, embedding critical insights into engineers' workflows. Observability Insights in Your Workflow: Get real-time insights and root cause analysis directly where you work, completely eliminating context switching. Intelligent Decision-Making: Leverage RAG a"
AI is transitioning from chat interfaces to agentic, autonomous systems that can analyze and act on operational data. The Model Context Protocol (MCP) establishes a standardized, bi-directional channel between large language models and external tools to avoid custom one-off integrations. New Relic introduced an MCP Server that enables MCP-compliant AI agents to access actionable observability data and embed insights into engineers' workflows. The integration allows popular AI assistants like GitHub Copilot, ChatGPT, Claude, and Cursor to retrieve detailed observability information in real time, reducing context switching. The approach aims to provide root cause analysis, intelligent decision-making, and safer connections between critical business workflows and observability-focused AI tools.
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