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New Relic▌

by newrelic

New Relic: unified observability platform for metrics, logs, traces and APM—get end-to-end visibility into application p

Access observability data including metrics, logs, traces, and entities

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Full observability stack accessReal-time monitoring data

best for

  • / DevOps engineers monitoring production systems
  • / Developers debugging performance issues
  • / Site reliability engineers tracking SLAs
  • / Teams building custom dashboards

capabilities

  • / Query application performance metrics
  • / Retrieve system logs and error data
  • / Access distributed tracing information
  • / Monitor infrastructure entities
  • / Fetch service health indicators
  • / Analyze performance trends

what it does

Connects to New Relic's observability platform to query application performance metrics, logs, traces, and infrastructure data.

about

New Relic is an official MCP server published by newrelic that provides AI assistants with tools and capabilities via the Model Context Protocol. New Relic: unified observability platform for metrics, logs, traces and APM—get end-to-end visibility into application p

how to install

You can install New Relic in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server supports remote connections over HTTP, so no local installation is required.

license

MIT

New Relic is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

FAQ

What is the New Relic MCP server?
New Relic is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for New Relic?
This profile displays 41 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 out of 5—verify behavior in your own environment before production use.

Use Cases▌

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

✓

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

✓

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

✓

Complete complex tasks end-to-end without manual steps

Implementation Guide▌

Prerequisites

  • ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • ›Basic understanding of MCP architecture and capabilities
  • ›Access credentials for integrated services (if required)
  • ›Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • ⚠MCP server not loading: Check config syntax, verify installation
  • ⚠Connection errors: Check network, firewall, credentials
  • ⚠Feature not working: Read server docs, check required parameters
  • ⚠Performance issues: Monitor resource usage, check for network latency
  • ⚠Conflicts with other servers: Check port assignments, namespace collisions

Best Practices▌

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • −Don't grant overly permissive access to MCP servers
  • −Don't skip reading security considerations in docs
  • −Don't expose sensitive data without proper controls
  • −Don't run untrusted MCP servers without code review
  • −Don't ignore error messages—investigate root cause

💡 Pro Tips

  • ★Combine multiple MCP servers for powerful workflows
  • ★Create custom MCP servers for your specific needs
  • ★Share successful configurations with team
  • ★Use MCP inspector for debugging
  • ★Join MCP community for tips and troubleshooting

Technical Details▌

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This▌

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration▌

  • →Tool composition: Chain multiple MCP tools in workflows
  • →Context augmentation: Provide AI with relevant external data
  • →Action delegation: Let AI execute tasks on external systems
  • →Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.7★★★★★41 reviews
  • ★★★★★Mia Liu· Dec 16, 2024

    We evaluated New Relic against two servers with overlapping tools; this profile had the clearer scope statement.

  • ★★★★★Kofi Patel· Dec 12, 2024

    We wired New Relic into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • ★★★★★Ren Singh· Dec 4, 2024

    New Relic reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • ★★★★★Ren Bhatia· Nov 23, 2024

    New Relic has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • ★★★★★William Singh· Nov 7, 2024

    New Relic is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • ★★★★★Ren Jain· Oct 14, 2024

    New Relic is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • ★★★★★Pratham Ware· Sep 21, 2024

    We evaluated New Relic against two servers with overlapping tools; this profile had the clearer scope statement.

  • ★★★★★Evelyn Abebe· Sep 5, 2024

    Strong directory entry: New Relic surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • ★★★★★Yuki Robinson· Aug 24, 2024

    Useful MCP listing: New Relic is the kind of server we cite when onboarding engineers to host + tool permissions.

  • ★★★★★Piyush G· Aug 12, 2024

    I recommend New Relic for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

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