Use Sentry Application Monitoring with your AI.
Connect your account once and let the AI you already use work with it, without building another integration. Grant your AI agent full access to Sentry's Application Performance Monitoring capabilities to track raw exceptions, resolve error logs, and inspect crash stack traces
Developed, maintained, and hosted by Vinkius.
MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED
Waiting for input…
Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.
Complete set · 10 capabilities
The complete Sentry Application Monitoring capability set.
These are the exact actions your AI can choose when you ask it to work with Sentry Application Monitoring.
01-04
4 capabilities in this set.
Part of 10 available through Sentry Application Monitoring.
- 01
List organization users
Lists all users in an organization
- 02
Delete issue
This action is irreversible. Permanently deletes an issue
- 03
Get event details
Retrieves details for a specific event
- 04
List events
Lists recent events for a project
05-07
3 capabilities in this set.
Part of 10 available through Sentry Application Monitoring.
- 05
Resolve issue
This is a reversible side-effect. Resolves an issue in Sentry
- 06
List organization teams
Lists all teams in an organization
- 07
List projects
Lists all projects in an organization
08-10
3 capabilities in this set.
Part of 10 available through Sentry Application Monitoring.
- 08
List organizations
Lists all Sentry organizations
- 09
Get issue details
Retrieves details for a specific issue
- 10
List issues
Lists all issues (errors) in a project
Observed, not estimated
878ms average. Fast in production.
Sentry Application Monitoring is checked daily against the live service.
- Fastest day
- 685ms
- Slowest day
- 1114ms
- 14-day trend
- Slowing+29%
Connect your client
One URL. Every client.
Activate the Connector, copy your link, and paste it into the client you already use. 10 capabilities arrive ready to run.
Preview access · not provider authentication
The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Sentry Application Monitoring, so you can see the experience inside your AI.
It does not authenticate your account with Sentry Application Monitoring. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.
Sentry Application Monitoring Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_44oqnI7Ime1XiKScWG9YlmefdW04ekDjWjnlXHRM/mcpClaude Desktop
Follow the steps below to connect in seconds.
- 1In Claude Desktop, open Settings → Connectors.
- 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
- 3Click Add and start a new chat — Sentry Application Monitoring capabilities are ready to use.
{
"mcpServers": {
"sentry-mcp": {
"url": "https://edge.vinkius.com/vk_preview_44oqnI7Ime1XiKScWG9YlmefdW04ekDjWjnlXHRM/mcp"
}
}
}
Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline
Step-by-step instructions for each client are in the guide. How to connect
FAQ
Questions Sentry Application Monitoring owners ask.
- 01
Can this AI integration actually mark errors as fixed?
Yes. This agent component possesses mutable write access. If you invoke the prompt properly, it will fire the resolve_issue capability, marking the corresponding exception ID completely dealt with inside the Sentry ecosystem. It can also erase bugs fully via delete_issue.
- 02
What is the difference between inspecting an 'Issue' and an 'Event'?
An 'Issue' gathers underlying multiple occurrences of the identical stack exception into one overarching master group. In contrast, querying an 'Event' (get_event_details) focuses the AI on a strictly singular, point-in-time incidence where the system crashed.
- 03
Do I need to supply the Organization Slug with every command?
You configure the overarching Organization Slug strictly at startup globally. For project-level filters, let your LLM query list_projects first to fetch internal slugs naturally into its memory buffer without constant repeated user inputs.
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