Intelligent observability leader gives enterprises the ability to observe agentic integrations leveraging MCP servers 

Enterprises can now understand AI performance within the context of the entire application stack, and quickly pinpoint issues across the AI layer, MCP tools and backend services  

MCP service providers gain visibility into how tools and resources are being used to optimize for overall system reliability

New Relic, the Intelligent Observability company, today announced groundbreaking support for the Model Context Protocol (MCP) within its comprehensive AI Monitoring solution, fully integrated with New Relic’s best-in-class Application Performance Monitoring (APM). Now developers building agents that use MCP and the teams providing MCP services can access deep, actionable insights that allow them to quickly pinpoint and resolve any issues with AI applications, reducing the need for manual effort and custom instrumentation, and lowering operational costs.

“Since it was released last year, MCP has quickly become the standard protocol for agentic AI. Once again meeting our customers where and how they work, our new MCP integration is a game-changer for anyone building or operating AI systems that rely on this protocol,” said New Relic Chief Technology Officer Siva Padisetty. “We’ve moved beyond siloed LLM monitoring to demystify MCP, connecting insights from AI interactions directly with the performance of the entire application stack for a holistic view. All this is offered as an integral part of our industry leading APM technology.”

MCP servers are critical for enabling AI agents to interact with various tools and services, but often operate as “black boxes.” This leads to a lack of visibility into which tools are being used by AI agents and how they perform. It’s also difficult for MCP providers to understand tool usage, identify performance bottlenecks or pinpoint error sources within their service. Often, complex, manual effort is required for custom instrumentation to get any insights.  

New Relic’s support for MCP solves these challenges, giving agent developers and MCP providers the following capabilities: 

• Instant MCP tracing visibility - Automatically uncover specific usage and patterns of the entire lifecycle of an MCP request, including invoked tools, call sequences, and execution durations with clear waterfall diagrams. 
• Proactive MCP optimization - Quickly analyze which tools agents select for specific prompts, evaluate tool choices and effectiveness, and track usage patterns, latency, errors, and performance to optimize MCP services and demonstrate value.
• Intelligent AI monitoring context - Seamlessly correlate MCP performance with the entire application ecosystem – including databases, microservices and queues – eliminating screen-swiveling between monitoring tools. 

New Relic AI Monitoring is part of New Relic intelligent observability platform and offered via its usage-based pricing model, which aligns cost with actual value delivered, in contrast to seat-based pricing. This comprehensive, all-in-one solution helps organizations find the root cause of AI application issues faster, furthers their adoption of AI, and supports them at every stage of their AI journey. According to New Relic’s recent AI Unwrapped: 2025 AI Impact Report, since its launch last year, enterprises have been adopting New Relic AI Monitoring at a steady 30% growth in usage quarter-over-quarter in the previous 12 months. As AI quickly becomes ingrained in their businesses, New Relic’s customers are increasingly seeking solutions to ensure model reliability, accuracy, compliance, and cost efficiency.

Availability 

New Relic AI Monitoring MCP support is part of the New Relic all-in-one intelligent platform and is now available in Python Agent version 10.13.0, with additional languages coming soon. Read more about it here.