Sentry provides APIs for error tracking, performance monitoring, and release management. AI agents can use Sentry to query errors, analyze crash reports, manage releases, and automate incident response.
What AI agents can do with Sentry
Structured actions an AI agent can execute through the Sentry API
Action
Description
Inputs
Outputs
listIssues
List error issues for a project
project_slug, query, sort, status
issues[], total_count
getIssue
Get details about a specific issue
issue_id
title, metadata, count, first_seen, last_seen, assignee
resolveIssue
Resolve or ignore an issue
issue_id, status, substatus
id, status
createRelease
Create a new release
organization, version, projects, refs
version, date_created
Use cases for Sentry + AI agents
- Automated error triage and assignment
- Incident response automation
- Release tracking and monitoring
- Error trend analysis
- On-call alert management
How to connect Sentry to an AI agent
- 1Get your Sentry API auth token
- 2Generate an AgentSpec for error tracking actions
- 3Define issue listing, detail, and resolution actions
- 4Publish for discovery
- 5Connect to your organization and projects
Best practices
✓Use query filters to scope issues by project and time range
✓Include reasoning docs about resolve vs ignore decisions
✓Track release health after deployments
✓Set up alert rules to trigger agent workflows
✓Use issue assignment for team routing
Frequently asked questions
Can AI agents triage Sentry errors?+
Yes. Agents can list issues, read stack traces, assign to team members, and resolve or ignore issues based on predefined rules and reasoning docs.
How do agents prioritize Sentry issues?+
Use the sort parameter (frequency, date, priority) and status filters. Agents can analyze error count, user impact, and recency to prioritize issues.
Can agents create Sentry releases?+
Yes. After a deployment, the agent can create a release with version info and commit references, then monitor the release for new issues.
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