AI-powered error triage and debugging with Sentry integration
The official Sentry MCP Server brings AI-powered error triage and debugging into your AI assistant. Query error events, inspect stack traces, analyze crash trends, and manage issue assignments directly through natural language.
Built by Sentry, the server connects to your Sentry organization using an auth token. It provides tools to search issues, view event details, examine breadcrumbs, and understand error frequency patterns.
Perfect for on-call engineers, SREs, and developers who want to quickly diagnose production errors without navigating the Sentry dashboard.
Valid MCP server (1 strong, 1 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.
4 files analyzed · No issues found
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Add this to your MCP configuration file:
{
"mcpServers": {
"sentry": {
"env": {
"SENTRY_AUTH_TOKEN": "<your-token>"
},
"args": [
"-y",
"@sentry/mcp-server"
],
"command": "npx"
}
}
}From the project's GitHub README.
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.
Install as a Claude Code plugin for automatic subagent delegation:
claude plugin marketplace add getsentry/sentry-mcp
claude plugin install sentry-mcp@sentry-mcp
This provides a sentry-mcp subagent that Claude automatically delegates to when you ask about Sentry errors, issues, traces, or performance.
For forward-looking tool variants and features:
claude plugin install sentry-mcp@sentry-mcp-experimental
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, search_issues, etc.) require an LLM provider (OpenAI or Anthropic). These tools use natural language processing to translate queries into Sentry's query syntax. Without a configured provider, 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
Need to connect to a self-hosted deployment? Add --host (hostname only, e.g. --host=sentry.example.com) when you run the command.
Some features (like Seer) may not be available on self-hosted instances. You can disable specific skills to prevent unsupported tools from being exposed:
npx @sentry/mcp-server@latest --access-token=TOKEN --host=sentry.example.com --disable-skills=seer
SENTRY_ACCESS_TOKEN= # Required: Your Sentry auth token
# LLM Provider Configuration (required for AI-powered search tools)
EMBEDDED_AGENT_PROVIDER= # Required: 'openai' or 'anthropic'
OPENAI_API_KEY= # Required if using OpenAI
ANTHROPIC_API_KEY= # Required if using Anthropic
# Optional overrides
SENTRY_HOST= # For self-hosted deployments
MCP_DISABLE_SKILLS= # Disable specific skills (comma-separated, e.g. 'seer')
Important: Always set EMBEDDED_AGENT_PROVIDER to explicitly specify your LLM provider. Auto-detection based on API keys alone is deprecated and will be removed in a future release. See docs/embedded-agents.md for detailed configuration options.
{
"mcpServers": {
"sentry": {
"command": "npx",
"args": ["@sentry/mcp-server"],
"env": {
"SENTRY_ACCESS_TOKEN": "your-token",
"EMBEDDED_AGENT_PROVIDER": "openai",
"OPENAI_API_KEY": "sk-..."
}
}
}
}
If you leave the host variable unset, the CLI automatically targets the Sentry SaaS service. Only set the override when you operate self-hosted Sentry.
For self-hosted instances that don't support Seer:
{
"mcpServers": {
"sentry": {
"command": "npx",
"args": ["@sentry/mcp-server"],
"env": {
"SENTRY_ACCESS_TOKEN": "your-token",
"SENTRY_HOST": "sentry.example.com",
"MCP_DISABLE_SKILLS": "seer"
}
}
}
}
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 and agent skills:
make setup-env # Creates .env files and installs shared agent skills
This also runs npx @sentry/dotagents install to install shared skills from getsentry/skills into .agents/skills/ (symlinked into .claude/skills and .cursor/skills). If you need to update skills later, run it directly:
npx @sentry/dotagents install
Create an OAuth App in Sentry (Settings => API => Applications):
http://localhost:5173http://localhost:5173/oauth/callbackConfigure your credentials:
.env in the root directory and add your OPENAI_API_KEYpackages/mcp-cloudflare/.env and add:
SENTRY_CLIENT_ID=your_development_sentry_client_idSENTRY_CLIENT_SECRET=your_development_sentry_client_secretCOOKIE_SECRET=my-super-secret-cookieStart 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 three test suites included: unit tests, evaluations, and manual testing.
Unit tests can be run using:
pnpm test
Evaluations 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
Manual testing (preferred for testing MCP changes):
# Test with local dev server (default: http://localhost:5173)
pnpm -w run cli "who am I?"
# Test agent mode (use_sentry tool only)
pnpm -w run cli --agent "who am I?"
# Test against production
pnpm -w run cli --mcp-host=https://mcp.sentry.dev "query"
# Test with local stdio mode (requires SENTRY_ACCESS_TOKEN)
pnpm -w run cli --access-token=TOKEN "query"
Note: The CLI defaults to http://localhost:5173. Override with --mcp-host or set MCP_URL environment variable.
Comprehensive testing playbooks:
docs/testing-stdio.md for complete guide on building, running, and testing the stdio implementation (IDEs, MCP Inspector)docs/testing-remote.md for complete guide on testing the remote server (OAuth, web UI, CLI client)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:
When addressing automated feedback, focus on the underlying concerns rather than strictly following every suggestion.
Looking to contribute or explore the full documentation map? See CLAUDE.md (also available as AGENTS.md) for contributor workflows and the complete docs index. The docs/ folder contains the per-topic guides and tool-integrated .md files.
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