Sentry MCP, Ready to Go
Use Sentry with Claude or Cursor to debug production crashes and analyze stack traces in real time with your AI agent.
No credit card required. Experience the power of this integration risk-free.
Investigate production errors and stack traces in real time.
Works with every AI agent you already use
…and any MCP-compatible client
How fast is the Sentry Connector?
Average time for the server to become ready for requests over the last 14 days, measured until the initialize / tools/list handshake completes. Metrics are updated daily between 00:00 and 04:00 UTC. Create a free account, use this Connector on Vinkius Cloud, and connect it to your AI agent in seconds.
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What AI agents can do with Sentry 10-Tool Production Error Tracking
Use these tools to fetch logs, analyze stack traces, manage issue statuses, and audit your Sentry organization structure.
Delete issue
The delete_issue tool permanently removes an issue from your project. Use it only for cleanup because this action is irreversible.
List events
The list_events tool lists recent events for a specific project. It helps you see the chronological flow of what's happening in your app.
Get event details
The get_event_details tool pulls the full details for a single event. It's the best way to see the specific metadata behind a single occurrence.
List organizations
The list_organizations tool shows all the organizations you have access to. This helps you navigate between different workspace environments.
List projects
The list_projects tool gets a list of all projects within an organization. Use this to scope your AI's search to a specific app or service.
Resolve issue
The resolve_issue tool marks an issue as resolved in Sentry. This helps keep your dashboard clean and signals that a bug is fixed.
List organization teams
The list_organization_teams tool lists all teams associated with an organization. This is useful for auditing permissions or looking up team structures.
List organization users
The list_organization_users tool lists all users in an organization. Use this to check who has access to your Sentry environment.
Get issue details
The get_issue_details tool pulls the full details and stack trace for a specific issue. This is the primary way to let your agent analyze a crash.
List issues
The list_issues tool lists all errors and issues in a project. Use this to find what's currently breaking in your production environment.
A Connector is a URL. Vinkius runs it: hosting, security, governance, observability.
You're looking at one of 5,800+ managed Connectors. The real value isn't the catalog. It's the control plane that secures, governs, audits, and manages every interaction between your agents and the tools they use.
No Shadow AI
Every agent action is visible, approved, and auditable. Nothing runs outside your governance.
Absolute agent control
Fine-grained permissions for every agent, MCP, and tool. Instantly revoke access and audit every execution.
Cost control per token
Spend broken down to the token, tool, and agent. Budgets and hard limits. No surprise invoices.
Managed & monitored infra
We operate the runtime, authentication, scaling, retries, and monitoring. Your team manages AI, not infrastructure.
Data protection, DLP by design
Sensitive data is filtered before reaching the model. Access is governed so agents receive only the information they're allowed to use.
Token optimization, real savings
Lower AI costs by delivering the right context instead of unnecessary tools. Better accuracy, faster responses, and fewer wasted tokens.
Sentry Error Tracking for Faster Debugging
The Sentry MCP is built for the engineers who live in the terminal and the ops teams who need to stop clicking through nested dashboards to find a single failing line of code.
On-call Engineer
They use this on Tuesday nights to quickly identify which production service is throwing the most errors and why.
Frontend Developer
They use this to pull specific crash traces into their chat window to see exactly what state caused a UI component to fail.
Technical Founder
They use this to ask for a high-level summary of critical bugs across all projects before a daily standup.
Frequently Asked Questions
How does the Sentry MCP help me debug faster? +
It allows your AI agent to pull real-time error logs and stack traces directly into your chat. You can ask questions about specific crashes and get immediate answers without leaving your workspace.
Can I use the Sentry MCP to manage my issues? +
Yes. You can tell your AI agent to mark issues as resolved or find specific ones in your project. It handles the manual clicking for you.
Does the Sentry MCP work with my current IDE? +
Yes. Since it's an Connector, it works with any compatible client like Cursor, Windsurf, or VS Code, giving you Sentry data right where you write code.
Is my Sentry data secure with this Connector? +
The Connector uses your own scoped Auth Token and Organization Slug. You control exactly what parts of your Sentry environment the AI can see.
Can the AI agent see my whole Sentry account? +
It depends on the permissions of the Auth Token you provide. You can scope it to specific projects or organizations to keep it limited.
What happens when I ask about a crash? +
The agent will search your project for recent errors, find the most relevant ones, and summarize the technical details and stack traces for you.
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 tool, marking the corresponding exception ID completely dealt with inside the Sentry ecosystem. It can also erase bugs fully via delete_issue.
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.
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.
Your AI, connected to everything.
No credit card required · Free tier available
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