Sentry MCP Integration

Weldable's Sentry MCP integration connects your AI agents to Sentry for monitoring errors, querying issues, and managing alerts through natural language. Sentry has built its own AI debugging agent called Seer, which handles root cause analysis and automated code fixes. Weldable extends Sentry's capabilities by letting your agents act on error data across your entire toolchain, connecting alerts to issue trackers, messaging platforms, and deployment systems in coordinated workflows.

Your agent speaks plain English. Ask it to check for new errors, get details on a specific issue, or list unresolved problems in a project, and Weldable routes the request to the right Sentry API endpoint.

Use cases

Automated error triage

Your agent queries Sentry for new unresolved issues in the last hour, groups them by frequency and affected service, and creates Jira or Linear tickets for anything above a threshold. Each ticket includes the error message, stack trace, first and last seen timestamps, and a direct link to the Sentry issue. This replaces the manual process of checking Sentry, deciding what needs a ticket, and copying details into your project tracker.

Incident alerting with context

When a new error spikes above its normal frequency, your agent pulls the issue details from Sentry and posts a structured alert to Slack. The alert includes the error type, the number of events in the last hour, affected users count, and the release where it first appeared. If the error is tied to a recent deployment, the agent cross-references the release with your GitHub commits to identify the likely culprit.

Release health monitoring

After each deployment, your agent queries Sentry for errors associated with the new release tag. It compares error rates against the previous release and generates a health report. If the new release shows a significant increase in errors, the agent posts a warning to Slack and creates a high-priority issue in your project tracker. Teams get early warning about regressions without watching dashboards manually.

Error trend analysis

Your agent pulls error data from Sentry on a weekly basis, identifies trends like increasing frequency or new error types, and compiles a report. It highlights which errors have been open the longest, which affect the most users, and which are growing fastest. Post the analysis to Google Docs or Slack to give the team a clear picture of where to focus debugging effort.

Customer-reported bug correlation

When a customer reports a bug through your support channel, your agent searches Sentry for matching errors based on the description. It pulls the stack trace, affected browser or device information, and event count, then attaches this technical context to the support ticket. This bridges the gap between what the customer describes and what the code is actually doing.

How it works

Connect your Sentry organization through an auth token. Weldable stores the credentials securely and handles token management. Your agent gets read and write access to projects, issues, and events based on the permissions you grant.

Describe what you need in natural language. Weldable matches your intent to the correct Sentry API endpoint, resolves organization and project slugs, and handles pagination for large result sets. Your agent can chain Sentry data with other integrations: detect an error, create a ticket, and notify the team in one continuous flow.

Tips

Filter by environment to reduce noise. Sentry tracks errors across environments like production, staging, and development. Tell your agent to focus on production errors when building alerts or reports. This prevents staging noise from triggering workflows that should only respond to real user impact.

Use release tags to correlate errors with deploys. Sentry associates errors with releases when you configure release tracking. Your agent can query errors by release version, making it easy to answer "did this deploy break anything" without manually filtering the dashboard.

Issue status matters for queries. Sentry issues can be unresolved, resolved, or ignored. Specify the status you want when querying to get relevant results. Asking for "unresolved errors in the last 24 hours" gives you actionable data instead of a mix of old and new problems.

Event counts indicate severity. The number of events for an issue tells you how many times the error has occurred. Your agent can use this metric to set priority levels when creating tickets: high event counts get high priority, low counts get triaged normally.

Sentry's API supports time-range filtering. Specify date ranges in your queries to scope results. This is especially useful for post-deploy checks and weekly reports where you only care about errors within a specific window.