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New Relic Adds MCP Support to Boost AI Observability and Insights

DevOps

New Relic Adds MCP Support to Enhance AI Observability

Business Honor
16 June, 2025

Integration enhances AI workflow monitoring, giving DevOps teams deeper insights into agent performance.

New Relic has enhanced its observability platform with support for the Model Context Protocol (MCP), enabling DevOps and IT operators to better understand artificial intelligence (AI) agents and applications.

Built by Anthropic, MCP is rapidly emerging as an industry-standard API for facilitating communication between AI agents and other data sources. With this new integration, New Relic is now able to monitor AI agents, tools, and processes with significantly more detail—alongside standard legacy applications.

New Relic formerly had observability for large language models (LLMs), but MCP takes that capability further. Teams can now monitor how AI agents engage with LLMs, such as prompt usage, tool calls, call sequences, and execution time. This provides developers and DevOps teams with a complete view of AI workflows.

The new functionality is available in Python Agent version 10.13.0, with support for additional programming languages on its way.

According to New Relic, usage of its AI monitoring tools has grown by 30% each quarter, with a 92% increase in unique AI models tracked. Interestingly, OpenAI’s ChatGPT models account for 86% of all LLM tokens used—a sign of OpenAI’s strong market presence.

Nic Benders, Chief Technical Strategist for New Relic, noted that observability will be used to enable organizations to know which AI models are deployed, when, and how. This will become crucial as companies try to balance cost, performance, and infrastructure compatibility.

As the use of AI continues to increase, tools such as New Relic's observability platform will become important in assisting developers and IT operations to monitor performance, minimize latency, and increase reliability.