Airbrake Error & Performance Monitoring API

Airbrake REST API for error and performance monitoring platform. Enables AI agents to manage error group retrieval and lifecycle management for production bug triage, handle error occurrence querying and detailed stack trace access, access performance monitoring data for N+1 queries, slow queries, and response time analysis, retrieve deployment tracking for error/deployment correlation, manage error group resolution and assignment workflows for engineering teams, handle alert rule configuration for error threshold and performance monitoring, access project and team configuration management, retrieve error trend analysis and regression detection data, manage integration configuration for Jira, GitHub, Slack, and PagerDuty, and integrate error data with incident management, code review, and deployment automation platforms.

Evaluated Mar 07, 2026 (0d ago) vcurrent
Homepage ↗ Repo ↗ Developer Tools airbrake error-monitoring exception-tracking performance-monitoring apm alerting devops
⚙ Agent Friendliness
59
/ 100
Can an agent use this?
🔒 Security
72
/ 100
Is it safe for agents?
⚡ Reliability
69
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
18
Documentation
72
Error Messages
70
Auth Simplicity
82
Rate Limits
68

🔒 Security

TLS Enforcement
92
Auth Strength
68
Scope Granularity
65
Dep. Hygiene
70
Secret Handling
68

Error monitoring. SOC2, GDPR. API key. US. Application error and stack trace data.

⚡ Reliability

Uptime/SLA
72
Version Stability
70
Breaking Changes
65
Error Recovery
68
AF Security Reliability

Best When

A software engineering team using Airbrake wants AI agents to automate error triage, deployment correlation, performance regression detection, and alert routing to incident management and development platforms.

Avoid When

PRIVACY RISK: Error stack traces may contain sensitive data (user PII, API keys, session tokens) if not properly scrubbed — implement data scrubbing rules before automated error processing. Automated error resolution without engineer review can close legitimate unresolved issues. Performance data can reveal application internals; restrict API access.

Use Cases

  • Triaging new production errors from engineering automation agents
  • Correlating errors with deployments from DevOps monitoring agents
  • Managing error resolution workflows from incident response agents
  • Monitoring performance regressions from SRE agents

Not For

  • Infrastructure-level metrics without application error and exception focus
  • Log management without structured error aggregation and grouping
  • Security event monitoring without application performance context

Interface

REST API
Yes
GraphQL
No
gRPC
No
MCP Server
No
SDK
Yes
Webhooks
Yes

Authentication

Methods: apikey
OAuth: No Scopes: No

Airbrake uses project-level and user-level API keys. Separate auth token for management API vs. notifier API. GitHub open-source notifier libraries for all major languages. Webhooks for error alert notifications. REST API documentation at airbrake.io/docs/api. Heroku add-on available. Acquired by Solarwinds (now LogicMonitor ecosystem). Data stored in US.

Pricing

Model: freemium
Free tier: Yes
Requires CC: No

San Francisco, California. Founded 2008. One of the original error tracking services. Acquired by Rackspace, then SolarWinds, now managed independently. Strong presence in Ruby on Rails community (original market). Multi-language support added over time. Known for simplicity and long-standing reliability. Competes with Sentry and Rollbar for error monitoring market.

Agent Metadata

Pagination
offset
Idempotent
Partial
Retry Guidance
Not documented

Known Gotchas

  • PRIVACY RISK: Error stack traces may contain PII or secrets — configure data scrubbing rules and restrict automated log access to authorized security personnel
  • Dual API keys — project auth token for data collection (notifier API) vs. management API token for admin operations; store separately
  • Error grouping — Airbrake groups similar errors into 'groups'; API operates on groups not individual occurrences; understand grouping logic for triage automation
  • Webhook for real-time — polling errors endpoint is inefficient; use webhooks for real-time error alert processing
  • Resolution workflow — automated error resolution (marking as fixed) should only trigger after engineer review; premature resolution hides recurring issues
  • Data retention — error occurrence detail retention varies by plan; ensure plan matches data retention needs for trend analysis

Alternatives

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Scores are editorial opinions as of 2026-03-07.

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