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Glama
MohamedSawahZC

newrelic-mcp

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": true
}
logging
{}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
extensions
{
  "io.modelcontextprotocol/ui": {}
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
nrql_queryA

Run a NRQL query against your New Relic account and return results.

Use this to query any telemetry data: transactions, errors, spans, logs, infrastructure metrics, custom events, etc.

nrql_batch_queryA

Run multiple NRQL queries in a single request (more efficient than individual calls).

search_entitiesB

Search for New Relic entities (applications, hosts, services, etc.).

get_entityA

Get detailed information about a specific entity by its GUID.

Returns entity metadata including type-specific info (APM language, host metrics, etc.).

get_alert_conditionsB

List NRQL alert conditions configured in your account.

get_open_incidentsA

Get all currently active (open) incidents/issues from New Relic AI.

Returns issues with their title, priority, affected entities, condition name, and policy name.

get_deploymentsC

Get recent deployments for an APM application entity.

get_golden_signalsB

Get golden signals for an APM app: throughput, error rate, latency, saturation.

get_error_tracesA

Get recent error traces for an application, including stack traces and messages.

get_throughput_timeseriesB

Get throughput over time for an application (useful for spotting traffic patterns).

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A3.5/5.0

Scored across 10 tools

Disambiguation4/5

Tools are mostly distinct: nrql_query and nrql_batch_query overlap in purpose but are clearly differentiated by efficiency, and search_entities vs get_entity serve different stages of entity interaction. Other tools each target a unique domain (alerts, incidents, deployments, golden signals, error traces, throughput), leaving little ambiguity.

Naming Consistency5/5

All tool names follow a consistent snake_case verb_noun pattern (e.g., get_entity, search_entities, nrql_query). The two nrql tools deviate slightly from get_ but still maintain the same structural style, making the naming predictable and coherent.

Tool Count5/5

With 10 tools, the server covers a broad but focused set of New Relic operations—querying, entity discovery, alerting, performance metrics, and deployment info. This is well-scoped for a monitoring MCP server, neither too sparse nor overloaded.

Completeness4/5

The surface covers core read-only workflows: flexible NRQL querying, entity lookup, alert/incident awareness, and APM performance details. Minor gaps exist (e.g., no log-specific query but nrql_query handles it, no entity mutation), but for a read-only monitoring server, it covers the essential needs without dead ends.

Maintenance

ActivityMaintained
ResponsivenessNo issues