Sentry Monitoring MCP for AI Agents. Query raw crash logs directly from your IDE.
Sentry gives your AI agent full, real-time access to your application's error logs and performance data. Instead of manually navigating dashboards to find crashes or stack traces, you simply ask your agent a question. It pulls the latest exceptions, diagnoses specific issues by feeding it context, and even marks resolved bugs as handled—all from within any MCP-compatible client.
Give Claude and any AI agent real-world access
The agent lists currently malfunctioning endpoints and functions, flagging fatal alerts in real time.
You provide an issue ID, and the agent retrieves the full stack trace along with environmental data for deep analysis.
The agent lists all projects or teams configured within your Sentry account.
You instruct the agent to mark a specific issue as handled, updating its status without manual web interaction.
Ask an AI about this
Waiting for input…
What AI agents can do with Sentry Monitoring MCP with 10 Tools
Use these tools to list active errors, retrieve detailed crash reports, manage projects, and automate the resolution of logged incidents.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Sentry MCPDelete Issue
Permanently removes an issue record from Sentry. Use with caution as this action cannot be undone.
List Events
Retrieves a chronological list of recent activity and events for a specific project.
Get Event Details
Pulls comprehensive details about one particular event, including all associated...
List Organizations
Displays a list of all Sentry organizations you have access to within the system.
List Projects
Retrieves all software projects contained within a specified organization.
Resolve Issue
Changes an issue's status to resolved, safely marking it as handled without needing the web interface.
List Organization Teams
Displays a list of all operational teams configured within your Sentry account.
List Organization Users
Retrieves every user registered across the entire organization's scope.
Get Issue Details
Fetches detailed information about a specific recorded bug or issue ID.
List Issues
Lists all active errors and open incidents within a designated project scope.
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Sentry, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,200+ others, all in one place
- Add new capabilities to your AI anytime you want
- Connections are secured and governed automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog weekly
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Sentry Application Monitoring. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on each call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
The pain of dashboard hopping Solved with Vinkius AI Gateway
Right now, finding out why your app crashed involves a painful dance across several tabs. You jump to the main dashboard, find an error ID, copy that ID over to another page to get more details, then maybe you have to open a separate window just to see which team owns it. It's a constant cycle of clicking, copying, and pasting.
With this MCP, your AI agent handles all that complexity for you. You simply ask the question—for instance, 'What was wrong with the payments endpoint?'—and the agent executes multiple underlying checks and delivers one clean answer right in your chat.
Get instant incident resolution via resolve_issue
Before this, fixing an issue meant a multi-step process: deploying the patch, waiting for confirmation, then manually going into Sentry's web UI to change the status from 'Open' to 'Resolved'. It was an administrative chore after doing all the hard coding work.
Now, once the fix is live and confirmed, you tell your agent to use resolve_issue. The status updates instantly through the API. You get to skip the clicks entirely—it’s just a command.
What your AI can actually do with this
This connector puts Sentry's entire operational monitoring suite directly into your chat window or IDE. You stop spending time combing through rigid crash dashboards just to figure out what broke last night. Your AI agent now treats your application logs like a searchable database, giving you immediate access to raw exceptions and the full stack trace context for any issue.
Need to know why a specific endpoint is throwing fatal alerts right now? You can ask your agent to list all current problems or dive deep into an existing bug using its ID. The system pulls the environmental metadata and reads the entire stack trace, telling you exactly which lines of code need attention.
Plus, if you've deployed a fix, you can tell the agent to close out that exception record—marking it resolved without having to click through the web interface. This level of direct control over production data is what Vinkius makes possible.
019d7606-15e8-705a-b07f-8fa255b79b92 Here's how it actually works
The bottom line is that your AI client acts like a direct API wrapper, turning complex monitoring tasks into simple conversation prompts.
Activate this MCP in your workflow configuration and securely provide your organization slug alongside your authentication token.
Prompt your AI client with a natural language question, such as 'What errors are happening on the user profile service right now?'
The agent executes the necessary tool calls to gather data (like listing issues or getting details) and presents the findings directly in the chat.
Who is this actually for?
This is for the DevOps engineer who wants to cut through dashboard noise and get actionable data instantly. It's for the software developer debugging late at night when every second counts, or the technical founder needing a rapid summary of product stability before a meeting.
You use this to check for spikes in latency across different servers, or quickly see if a recent deployment caused an unexpected surge in errors.
You ask the agent to pull up the variable state and stack trace for a specific failure ID so you can pinpoint the exact line of code that broke production.
You casually prompt the chatbot for a summary of all high-priority, open bugs across every startup project before your daily standup.
What Changes When You Connect
Get instant visibility into active errors. Instead of clicking through pages, you ask the agent to run list_issues and immediately see which endpoints are throwing fatal alerts.
Deeply analyze crashes without leaving your chat client. By sending an issue ID for get_issue_details, your AI agent devours the full stack trace and environmental context, pointing out exactly where the code failed.
Automate bug lifecycle management. You can use resolve_issue to safely close records once a fix is deployed, eliminating manual status updates in the web dashboard.
Understand system scope quickly. Use list_projects or list_organization_teams to map out which software branches and teams exist across your entire organization structure.
Speed up incident response. When an error occurs, you don't need to copy a massive stack trace into a ticket; the agent pulls the complete details for you.
See it in action
Pinpointing a mysterious production failure
A developer notices high latency. They ask their agent to list_issues across the affected project. The agent replies by showing 5 repeating 'TypeError' alerts, allowing the developer to immediately use get_issue_details on the top alert ID for the precise code line.
Managing post-deployment cleanup
The DevOps team pushes a patch and knows an old bug is fixed. They prompt the agent, 'Mark this issue as resolved.' The agent uses resolve_issue, updating the record instantly and stopping the alerts.
Auditing user access after a security incident
A manager needs to know who has access to sensitive data. They ask the agent to list_organization_users, getting an immediate roster of all accounts in the entire organization.
Debugging multi-service interactions
The engineer suspects a conflict between two services. They prompt the agent to list_projects and then get_event_details for both projects' latest events, correlating the timestamps to find the collision point.
The honest tradeoffs
What to watch out for, and the recommended way to handle each one.
Searching by keyword
Asking the chatbot, 'Tell me about authentication errors.' This forces the AI to guess which data set you mean and limits its scope.
Instead, ask the agent to list_issues for the specific service. Then, provide a clear follow-up: 'Focus only on issues related to JWT tokens within that list.'
Copying raw logs
Manually copying dozens of lines from a web dashboard into a ticket system because you can't see the full context.
Ask the agent to get_issue_details using the specific issue ID. This pulls the entire, structured stack trace and environmental metadata automatically.
Assuming scope
Asking for 'all bugs' without defining which project or organization you mean.
Always start by scoping your request. First, use list_projects to confirm the correct silo, then ask the agent to list_issues within that confirmed project.
When It Fits, When It Doesn't
Use this MCP if your primary need is real-time, actionable data access and workflow automation around production errors. If you are stuck on a bug at 2 AM and have to copy/paste dozens of lines or click through five different dashboards just to get context, this is for you. You want the AI client to do the legwork and give you the full stack trace instantly.
Don't use this if your requirement is simply historical reporting (e.g., 'Give me a chart showing error trends over 6 months'). For that, you need a dedicated analytics platform or BI tool. This MCP excels at investigation and action, not long-term trend visualization.
Questions you might have
Can Sentry MCP list all active open bugs? +
Yes, you can use list_issues to retrieve a comprehensive roster of every currently flagged error within a specific project. This lets you see which endpoints are throwing fatal alerts right now.
How do I get full stack trace details using Sentry MCP? +
You provide the agent with an issue ID, and it uses get_issue_details to pull every piece of metadata available, including the entire stack trace. This is crucial for debugging.
Is deleting issues via Sentry MCP permanent? +
Yes, using delete_issue permanently removes an issue record and this action cannot be reversed. Use it only after confirming you no longer need the data.
Can I find out what projects are configured in my account? +
Absolutely. You can use list_projects to get a clean list of every project within your organization's silo, helping you scope your investigation correctly.
Does Sentry MCP help with team structure? +
Yes, the agent provides tools like list_organization_teams and list_organization_users, allowing you to map out who is on which team within the organization.