piekstra/newrelic-mcp-server
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The New Relic MCP Server provides programmatic access to New Relic APIs, enabling AI assistants and other tools to interact with New Relic monitoring and observability data.
New Relic MCP Server
A Model Context Protocol (MCP) server that provides programmatic access to New Relic APIs, enabling AI assistants and other tools to interact with New Relic monitoring and observability data.
Features
- APM Application Management: List and retrieve application details, metrics, and metric data
- NRQL Queries: Execute NRQL queries via NerdGraph
- Log Parsing Rules: Intelligently create, manage, and test GROK patterns for log parsing
- Alert Policies: List and manage alert policies
- Synthetic Monitoring: Access synthetic monitor information
- Dashboards: List and retrieve dashboard configurations
- Entity Search: Search across all New Relic entities
- Infrastructure: Monitor servers and infrastructure components
- Deployments: Track and create application deployments
- User Management: List and manage users
- NerdGraph: Execute custom GraphQL queries
Installation
Option 1: Install from PyPI (Recommended)
pip install newrelic-mcp-server
Option 2: Install from Source
# Clone this repository
git clone https://github.com/piekstra/newrelic-mcp-server.git
cd newrelic-mcp-server
# Install in development mode
pip install -e .
Configuration
Secure Credential Setup (Recommended for macOS)
For enhanced security on macOS, use the built-in keychain storage instead of environment variables:
# Run the secure setup wizard
newrelic-mcp-setup
# Or set up manually with Python
python -m newrelic_mcp.credentials
This will securely store your API key and account ID in the macOS Keychain, eliminating the need to store sensitive credentials in plain text files.
Environment Variables (Alternative)
If you prefer environment variables or are not on macOS, you can use:
# Required
export NEWRELIC_API_KEY="your-api-key-here" # Your New Relic User API key
# Optional
export NEWRELIC_REGION="US" # or "EU" (default: "US")
export NEWRELIC_ACCOUNT_ID="your-account-id" # Required for some operations
Note: The server will automatically prefer keychain storage over environment variables when both are available.
Getting Your API Key
- Log in to New Relic
- Navigate to the API Keys page
- Create a new User API key (starts with
NRAK
) - Copy the key and set it as the
NEWRELIC_API_KEY
environment variable
Usage
With Claude Desktop
Option 1: Using Secure Keychain (Recommended for macOS)
After setting up credentials with newrelic-mcp-setup
, add the following to your Claude Desktop configuration (claude_desktop_config.json
):
{
"mcpServers": {
"newrelic": {
"command": "newrelic-mcp-server",
"env": {
"NEWRELIC_REGION": "US"
}
}
}
}
Option 2: Using Environment Variables (Less Secure)
{
"mcpServers": {
"newrelic": {
"command": "newrelic-mcp-server",
"env": {
"NEWRELIC_API_KEY": "your-api-key-here",
"NEWRELIC_REGION": "US",
"NEWRELIC_ACCOUNT_ID": "your-account-id"
}
}
}
}
Security Note: Option 1 is strongly recommended as it keeps your sensitive API key out of configuration files.
With Other MCP Clients
# Start the server directly
newrelic-mcp-server
# Or run as a module
python -m newrelic_mcp
Available Tools
Application Management
list_applications
- List all APM applicationsget_application
- Get details for a specific applicationget_application_metrics
- Get available metrics for an applicationget_application_metric_data
- Get metric data with time range filtering
Querying
query_nrql
- Execute NRQL queries for data analysisnerdgraph_query
- Execute custom NerdGraph GraphQL queries
Monitoring
list_alert_policies
- List all alert policiesget_alert_policy
- Get specific alert policy detailslist_synthetic_monitors
- List synthetic monitorsget_synthetic_monitor
- Get synthetic monitor details
Dashboards & Visualization
list_dashboards
- List all dashboardsget_dashboard
- Get dashboard configuration and widgets
Infrastructure
list_servers
- List monitored serversget_server
- Get server detailssearch_entities
- Search across all entity types
Deployment Tracking
list_deployments
- List application deploymentscreate_deployment
- Record new deployments
User Management
list_users
- List account usersget_user
- Get user details
Log Parsing Rules
list_log_parsing_rules
- List all log parsing rules for an accountcreate_log_parsing_rule
- Create a new log parsing rule with GROK pattern and NRQL filterupdate_log_parsing_rule
- Update an existing log parsing ruledelete_log_parsing_rule
- Delete a log parsing ruletest_log_parsing_rule
- Test a GROK pattern against sample logs (generates pattern if not provided)generate_log_parsing_rule
- Intelligently generate GROK patterns from log samples or NRQL queries
Credential Management
manage_credentials
- Securely manage API credentials in keychainaction="status"
- Show current credential storage statusaction="store"
- Store new credentials securely (requiresapi_key
parameter)action="delete"
- Remove all stored credentials
Examples
Query Application Performance
# List all applications
await list_applications()
# Get specific application metrics
await get_application_metric_data(
app_id='123456',
metric_names=['HttpDispatcher', 'Apdex'],
from_time='2024-01-01T00:00:00Z',
to_time='2024-01-02T00:00:00Z'
)
Execute NRQL Query
await query_nrql(
account_id='1234567',
nrql='SELECT average(duration) FROM Transaction WHERE appName = "My App" SINCE 1 hour ago'
)
Search Entities
await search_entities(
query='name LIKE "%production%"',
limit=50
)
Create Deployment Marker
await create_deployment(
app_id='123456',
revision='v2.0.1',
description='Production deployment',
user='deploy-bot',
changelog='Fixed critical bug in payment processing'
)
Log Parsing Rules
Generate GROK Pattern from Log Samples
# Generate parsing rule from sample logs (sanitized example)
await generate_log_parsing_rule(
log_samples=[
"Updated info for user 12345678-1234-5678-9012-123456789012 (updated 1 rows, expected 1) - updated values: EmailAddress test@example.com, FirstName TestName, LastName TestLast, Active True, EmailConfirmed False"
]
)
# Returns generated GROK pattern and NRQL filter:
# {
# "grok_pattern": "Updated info for user %{UUID:user_id:string} \\(updated %{INT:rows_affected:long} rows, expected %{INT:rows_expected:long}\\) - updated values: EmailAddress %{DATA:email:string}, FirstName %{WORD:first_name:string}, LastName %{WORD:last_name:string}, Active %{WORD:active:string}, EmailConfirmed %{WORD:emailconfirmed:string}",
# "nrql_pattern": "SELECT * FROM Log WHERE message LIKE 'Updated info for user % (updated % rows, expected %) - updated values: EmailAddress %, FirstName %, LastName %, Active %, EmailConfirmed %'",
# "suggested_description": "Auto-generated parsing rule for single log sample"
# }
Create Log Parsing Rule
# Create a new parsing rule using generated patterns
await create_log_parsing_rule(
description="User update audit log parsing",
grok="Updated info for user %{UUID:user_id:string} \\(updated %{INT:rows_affected:long} rows, expected %{INT:rows_expected:long}\\) - updated values: EmailAddress %{DATA:email:string}, FirstName %{WORD:first_name:string}, LastName %{WORD:last_name:string}, Active %{WORD:active:string}, EmailConfirmed %{WORD:emailconfirmed:string}",
nrql="SELECT * FROM Log WHERE message LIKE 'Updated info for user % (updated % rows, expected %) - updated values: EmailAddress %, FirstName %, LastName %, Active %, EmailConfirmed %'",
enabled=True
)
Generate from Live Logs
# Generate patterns from logs matching a query
await generate_log_parsing_rule(
log_query="service = 'user-service' AND message LIKE '%Updated info for user%'",
time_range="1 day ago",
field_hints={"user_id": "UUID", "email": "EMAIL"}
)
Test Parsing Rules
# Test a GROK pattern against samples
await test_log_parsing_rule(
log_samples=["Updated info for user 12345678-1234-5678-9012-123456789012 (updated 1 rows, expected 1)"],
grok_pattern="Updated info for user %{UUID:user_id:string} \\(updated %{INT:rows_affected:long} rows, expected %{INT:rows_expected:long}\\)"
)
Manage Parsing Rules
# List all parsing rules
await list_log_parsing_rules()
# Update a rule
await update_log_parsing_rule(
rule_id="12345",
description="Updated user audit log parsing",
enabled=False
)
# Delete a rule
await delete_log_parsing_rule(rule_id="12345")
Development
# Clone the repository
git clone https://github.com/piekstra/newrelic-mcp-server.git
cd newrelic-mcp-server
# Install in development mode
pip install -e .[dev]
# Install pre-commit hooks
pre-commit install
# Run the server
newrelic-mcp-server
# Run tests (when available)
pytest
# Format code
black newrelic_mcp
# Lint code
flake8 newrelic_mcp
# Run all pre-commit checks
pre-commit run --all-files
Dependencies
fastmcp
- FastMCP framework for building MCP servershttpx
- Async HTTP client for API requestspython-dotenv
- Environment variable management (optional)
API Rate Limits
Be aware of New Relic's API rate limits:
- REST API v2: Subject to rate limiting per account
- NerdGraph: Higher rate limits but still enforced
- Synthetic Monitoring API: 3 requests per second
Security
- Use keychain storage on macOS: Run
newrelic-mcp-setup
to store credentials securely in the system keychain - Never commit API keys to version control
- Avoid storing sensitive credentials in plain text configuration files
- API keys should have minimal required permissions
- Consider using separate keys for different environments
- The server automatically prioritizes keychain storage over environment variables for enhanced security
Troubleshooting
Authentication Errors
- Ensure your API key starts with
NRAK
- Verify the key has the necessary permissions
- Check if you're using the correct region (US/EU)
- If using keychain storage, verify credentials are stored with
manage_credentials
action="status" - Try re-running
newrelic-mcp-setup
if keychain access fails
Rate Limiting
If you encounter rate limit errors:
- Implement exponential backoff in your client code
- Cache frequently accessed data
- Batch operations where possible
Connection Issues
- Verify network connectivity
- Check firewall rules for API endpoints
- Ensure correct base URLs for your region
Python Environment
- Ensure Python 3.10+ is installed
- Install dependencies with
pip install -r requirements.txt
- Check that the script is executable:
chmod +x newrelic_mcp_server.py
Command Not Found Issues
If you encounter "command not found" errors after installation:
- Try using the full path to the installed package:
- Linux/macOS (user install):
~/.local/bin/newrelic-mcp-server
- macOS (Python framework):
/Library/Frameworks/Python.framework/Versions/3.13/bin/newrelic-mcp-server
- System-wide:
/usr/local/bin/newrelic-mcp-server
- Linux/macOS (user install):
- Or add the installation directory to your PATH:
export PATH="$HOME/.local/bin:$PATH"
- In Claude Desktop config, use the full path if the command isn't found:
{ "mcpServers": { "newrelic": { "command": "/Library/Frameworks/Python.framework/Versions/3.13/bin/newrelic-mcp-server", "env": { "NEWRELIC_API_KEY": "your-api-key-here", "NEWRELIC_REGION": "US", "NEWRELIC_ACCOUNT_ID": "your-account-id" } } } }
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
MIT
Support
For issues and questions:
- GitHub Issues: Create an issue
- New Relic Documentation: docs.newrelic.com