Intelligent Observability Leaders Give Enterprises the ability to observe agent integrations that leverage MCP servers
Enterprises can now understand AI performance within the context of the entire application stack and quickly identify issues across AI layers, MCP tools, and backend services.
MCP service providers gain visibility into how tools and resources are used to optimize system-wide reliability
New Relic, an intelligent observability company, today announced groundbreaking support for Model Context Protocol (MCP) within a comprehensive AI monitoring solution. Developers who currently use MCP and teams providing MCP services have access to deep and actionable insights to quickly identify and resolve issues with AI applications, reduce manual effort and the need for custom instruments, and reduce operational costs.
“Since its release last year, MCP has quickly become the standard protocol for Agent AI. To meet again where and how customers will function again, the new MCP integration is a game changer for those building or operating AI systems that rely on this protocol.” “We moved MCP to DemyStify beyond Sild LLM monitoring, combining insights from AI interactions directly with overall application stack performance and overall view performance. This is provided as an integral part of industry-leading APM technology.”
MCP servers are important to enable AI agents to interact with a variety of tools and services, but often act as “black boxes.” This leads to the lack of visibility of the AI agents using the tool and their performance. It is also difficult for MCP providers to understand the use of tools, identify performance bottlenecks within the service, and identify error sources. In many cases, custom instrumentation requires complex and manual effort to gain insight.
New Relic's support for MCP solves these challenges and provides agent developers and MCP providers with the following features:
- Instant MCP Trace Visibility – Automatically reveals specific uses and patterns throughout the lifecycle of an MCP request, including invoked tools, call sequences, and execution periods using clearwaterfall diagrams.
- Proactive MCP Optimization – Quickly analyze tools for selecting a specific prompt, assess tool selection and effectiveness, track usage patterns, latency, errors, and performance to optimize MCP services and demonstrate value.
- Intelligent AI Monitoring Context – Seamlessly correlates MCP performance with the entire application ecosystem, including databases, microservices, and queues, eliminating screen sowering between monitoring tools.
The new RELIC AI monitoring is part of the new Relic Intelligent Observability Platform and is provided via a usage-based pricing model that aligns costs with real value, as opposed to sheet-based pricing. This comprehensive all-in-one solution helps organizations to discover the root causes of AI application problems faster, promote adoption of AI, and support them at every stage of their AI journey. According to New Relic's recent AI Undrapped: 2025 AI Impact Report, since its launch last year, companies have adopted new RELIC AI monitoring with a steady 30% growth per quarter in the last 12 months. With AI quickly immersed in the business, New Relic customers are increasingly looking for solutions to ensure the reliability, accuracy, compliance and cost-effectiveness of their models.
availability
New RELIC AI Monitoring MCP support is part of the new Relic All-in-One Intelligent Platform and is now available with Python Agent version 10.13.0. For more information, please click here.
Maximizing Cloud Efficiency – Lumen Webinar April 23, 2025
According to KPMG, companies typically spend 35% more on the cloud than they need to provide business goals
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