Sentry's MCP service is primarily designed for human-in-the-loop coding agents. Our tool selection and priorities are focused on developer workflows and debugging use cases, rather than providing a general-purpose MCP server for all Sentry functionality.
This remote MCP server acts as middleware to the upstream Sentry API, optimized for coding assistants like Cursor, Claude Code, and similar development tools. It's based on Cloudflare's work towards remote MCPs.
You'll find everything you need to know by visiting the deployed service in production:
If you're looking to contribute, learn how it works, or to run this for self-hosted Sentry, continue below.
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.
Note: The AI-powered search tools (search_events
and search_issues
) require an OpenAI API key. These tools use natural language processing to translate queries into Sentry's query syntax. Without the API key, these specific tools will be unavailable, but all other tools will function normally.
To utilize the stdio
transport, you'll need to create an User Auth Token in Sentry with the necessary scopes. As of writing this is:
org:read
project:read
project:write
team:read
team:write
event:write
Launch the transport:
npx @sentry/mcp-server@latest --access-token=sentry-user-token --host=sentry.example.com
Note: You can also use environment variables:
SENTRY_ACCESS_TOKEN=
SENTRY_HOST=
OPENAI_API_KEY= # Required for AI-powered search tools (search_events, search_issues)
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
.
To contribute changes, you'll need to set up your local environment:
-
Set up environment files:
make setup-env # Creates both .env files from examples
-
Create an OAuth App in Sentry (Settings => API => Applications):
- Homepage URL:
http://localhost:5173
- Authorized Redirect URIs:
http://localhost:5173/callback
- Note your Client ID and generate a Client secret
- Homepage URL:
-
Configure your credentials:
- Edit
.env
in the root directory and add yourOPENAI_API_KEY
- Edit
packages/mcp-cloudflare/.env
and add:SENTRY_CLIENT_ID=your_development_sentry_client_id
SENTRY_CLIENT_SECRET=your_development_sentry_client_secret
COOKIE_SECRET=my-super-secret-cookie
- Edit
-
Start the development server:
pnpm dev
Run the server locally to make it available at http://localhost:5173
pnpm dev
To test the local server, enter http://localhost:5173/mcp
into Inspector and hit connect. Once you follow the prompts, you'll be able to "List Tools".
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 in the project root with some config:
# .env (in project root)
OPENAI_API_KEY= # Also required for AI-powered search tools in production
Note: The root .env
file provides defaults for all packages. Individual packages can have their own .env
files to override these defaults during development.
Once that's done you can run them using:
pnpm eval
This repository uses automated code review tools (like Cursor BugBot) to help identify potential issues in pull requests. These tools provide helpful feedback and suggestions, but we do not recommend making these checks required as the accuracy is still evolving and can produce false positives.
The automated reviews should be treated as:
- ✅ Helpful suggestions to consider during code review
- ✅ Starting points for discussion and improvement
- ❌ Not blocking requirements for merging PRs
- ❌ Not replacements for human code review
When addressing automated feedback, focus on the underlying concerns rather than strictly following every suggestion.