sentry-mcp

MCP.Pizza Chef: getsentry

sentry-mcp is an MCP server that acts as a middleware interface to the Sentry API, enabling large language models to interact with Sentry's error monitoring and event tracking services. It supports both remote and stdio transports, facilitating integration with self-hosted or cloud Sentry instances. This server allows real-time, structured access to Sentry data for enhanced AI-driven workflows and automation.

Use This MCP server To

Query Sentry error events using natural language via LLMs Automate incident summaries from Sentry event data Integrate Sentry monitoring data into AI-powered developer tools Enable LLMs to fetch and analyze Sentry project health metrics Support self-hosted Sentry with stdio transport for local MCP access Trigger alerts or workflows based on Sentry event context Aggregate and filter Sentry issues through AI-driven queries

README

sentry-mcp

codecov smithery badge

This is a prototype of a remote MCP sever, acting as a middleware to the upstream Sentry API provider.

It is based on Cloudflare's work towards remote MCPs.

Getting Started

You'll find everything you need to know by visiting the deployed service in production:

https://mcp.sentry.dev

If you're looking to contribute, learn how it works, or to run this for self-hosted Sentry, continue below..

Stdio vs Remote

While this repository is focused on acting as an MCP service, we also support a stdio transport. This is still a work in progress, but is the easiest way to adapt run the MCP against a self-hosted Sentry install.

To utilize the stdoio transport, you'll need to create an Personal API Token (PAT) in Sentry with the necessary scopes. As of writing this is:

org:read
project:read
project:write
team:read
team:write
event:read

Launch the transport:

npx @sentry/mcp-server@latest --access-token=sentry-pat --host=sentry.example.com

Note: You can also use environment variables:

SENTRY_AUTH_TOKEN=
SENTRY_HOST=

MCP Inspector

MCP includes an Inspector, to easily test the service:

pnpm inspector

Enter the MCP server URL (http://localhost:5173) and hit connect. This should trigger the authentication flow for you.

Note: If you have issues with your OAuth flow when accessing the inspector on 127.0.0.1, try using localhost instead by visiting http://localhost:6274.

Local Development

If you'd like to iterate and test your MCP server, you can do so in local development. This will require you to create another OAuth App in Sentry (Settings => API => Applications):

  • For the Homepage URL, specify http://localhost:8788
  • For the Authorized Redirect URIs, specify http://localhost:8788/callback
  • Note your Client ID and generate a Client secret.
  • Create a .dev.vars file in your project root with:
SENTRY_CLIENT_ID=your_development_sentry_client_id
SENTRY_CLIENT_SECRET=your_development_sentry_client_secret

Verify

Run the server locally to make it available at http://localhost:8788

pnpm dev

To test the local server, enter http://localhost:8788/sse into Inspector and hit connect. Once you follow the prompts, you'll be able to "List Tools".

Tests

There are two test suites included: basic unit tests, and some evaluations.

Unit tests can be run using:

pnpm test

Evals will require a .env file with some config:

OPENAI_API_KEY=

Once thats done you can run them using:

pnpm test

Notes

Using Claude and other MCP Clients

When using Claude to connect to your remote MCP server, you may see some error messages. This is because Claude Desktop doesn't yet support remote MCP servers, so it sometimes gets confused. To verify whether the MCP server is connected, hover over the 🔨 icon in the bottom right corner of Claude's interface. You should see your tools available there.

Using Cursor and other MCP Clients

To connect Cursor with your MCP server, choose Type: "Command" and in the Command field, combine the command and args fields into one (e.g. npx mcp-remote@latest https://<your-worker-name>.<your-subdomain>.workers.dev/sse).

Note that while Cursor supports HTTP+SSE servers, it doesn't support authentication, so you still need to use mcp-remote (and to use a STDIO server, not an HTTP one).

You can connect your MCP server to other MCP clients like Windsurf by opening the client's configuration file, adding the same JSON that was used for the Claude setup, and restarting the MCP client.

sentry-mcp FAQ

How do I connect sentry-mcp to my Sentry instance?
You configure sentry-mcp with your Sentry API credentials and endpoint, supporting both cloud and self-hosted setups.
What transport methods does sentry-mcp support?
It supports remote HTTP transport and an in-progress stdio transport for local self-hosted Sentry integration.
Can sentry-mcp handle multiple Sentry projects?
Yes, it can query and interact with multiple projects configured within your Sentry environment.
Is sentry-mcp compatible with different LLM providers?
Yes, it works with OpenAI, Anthropic Claude, and Google Gemini models via the MCP protocol.
How secure is the data exchange with sentry-mcp?
sentry-mcp uses scoped API access and secure transport channels to protect your Sentry data during interactions.
Can I extend sentry-mcp to support custom Sentry API endpoints?
Yes, the server is designed to be extensible to cover additional Sentry API features as needed.
Does sentry-mcp provide real-time event updates?
It can fetch the latest event data on demand but does not currently support push-based real-time streaming.
How do I deploy sentry-mcp for production use?
You can deploy it using the provided Docker images or source code, with configuration for your Sentry environment.