--- slug: "sentry-mcp" source_type: "readme" source_url: "https://cdn.jsdelivr.net/gh/getsentry/sentry-mcp@main/README.md" repo: "https://github.com/getsentry/sentry-mcp" source_file: "README.md" branch: "main" --- # sentry-mcp 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](https://blog.cloudflare.com/remote-model-context-protocol-servers-mcp/). ## Getting Started 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. ### Claude Code Plugin Install as a Claude Code plugin for automatic subagent delegation: ```shell 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: ```shell claude plugin install sentry-mcp@sentry-mcp-experimental ``` ### 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. **Note:** The AI-powered search tools (`search_events`, `search_issues`, etc.) require an LLM provider (OpenAI, Azure OpenAI, Anthropic, or OpenRouter). 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: ```shell 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. For isolated internal deployments that only expose plain HTTP, also add --insecure-http. Some features (like Seer) may not be available on self-hosted instances. You can disable specific skills to prevent unsupported tools from being exposed: ```shell npx @sentry/mcp-server@latest --access-token=TOKEN --host=sentry.example.com --disable-skills=seer ``` For self-hosted instances without TLS: ```shell npx @sentry/mcp-server@latest --access-token=TOKEN --host=sentry.internal:9000 --insecure-http ``` #### Remote with an Explicit Sentry Token Remote clients that support custom HTTP headers can pass an upstream Sentry API token directly to the Cloudflare transport: ```json { "mcpServers": { "sentry": { "url": "https://mcp.sentry.dev/mcp", "headers": { "Authorization": "Sentry-Bearer ${SENTRY_ACCESS_TOKEN}" } } } } ``` `Sentry-Bearer` is intentionally separate from `Bearer`: `Bearer` is reserved for MCP OAuth access tokens. With `Sentry-Bearer`, the worker does not store, validate, exchange, or refresh the upstream token. It forwards the token through the same Sentry API calls used by OAuth-backed sessions, and the client or upstream provider remains responsible for token lifetime and refresh. Direct remote auth defaults to all active MCP skills. You can narrow the exposed tools with `?skills=inspect,triage` or `?disable-skills=seer`. #### Environment Variables ```shell SENTRY_ACCESS_TOKEN= # Required: Your Sentry auth token # LLM Provider Configuration (required for AI-powered search tools) EMBEDDED_AGENT_PROVIDER= # Required when multiple provider keys are set: 'openai', 'azure-openai', 'anthropic', or 'openrouter' OPENAI_API_KEY= # Required if using OpenAI ANTHROPIC_API_KEY= # Required if using Anthropic OPENROUTER_API_KEY= # Required if using OpenRouter OPENROUTER_MODEL= # Optional OpenRouter model, defaults to 'openai/gpt-5' # 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/operations/embedded-agents.md](https://github.com/getsentry/sentry-mcp/blob/HEAD/docs/operations/embedded-agents.md) for detailed configuration options. #### Example MCP Configuration ```json { "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: ```json { "mcpServers": { "sentry": { "command": "npx", "args": ["@sentry/mcp-server"], "env": { "SENTRY_ACCESS_TOKEN": "your-token", "SENTRY_HOST": "sentry.example.com", "MCP_DISABLE_SKILLS": "seer" } } } } ``` ### MCP Inspector MCP includes an [Inspector](https://modelcontextprotocol.io/docs/tools/inspector), to easily test the service: ```shell pnpm inspector ``` Enter the MCP server URL () 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 To contribute changes, you'll need to set up your local environment: 1. **Set up environment and agent skills:** ```shell 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](https://github.com/getsentry/skills) into `.agents/skills/` (symlinked into `.claude/skills` and `.cursor/skills`). If you need to update skills later, run it directly: ```shell npx @sentry/dotagents install ``` 2. **Create an OAuth App in Sentry** (Settings => API => [Applications](https://sentry.io/settings/account/api/applications/)): - Homepage URL: `http://localhost:5173` - Authorized Redirect URIs: `http://localhost:5173/oauth/callback` - Note your Client ID and generate a Client secret 3. **Configure your credentials:** - Edit `.env` in the root directory and add either `OPENAI_API_KEY` or `OPENROUTER_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` 4. **Start the development server:** ```shell pnpm dev ``` ### Verify Run the server locally to make it available at `http://localhost:5173` ```shell 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". ### Tests There are three test suites included: unit tests, evaluations, and manual testing. **Unit tests** can be run using: ```shell pnpm test ``` **Evaluations** require a `.env` file in the project root with some config: ```shell # .env (in project root) OPENAI_API_KEY= # Use OpenAI-backed AI-powered tools OPENROUTER_API_KEY= # Or use OpenRouter-backed AI-powered tools ``` 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: ```shell pnpm eval ``` **Manual testing** (preferred for testing MCP changes): ```shell # 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:** - **Stdio testing:** See `docs/testing/stdio.md` for complete guide on building, running, and testing the stdio implementation (IDEs, MCP Inspector) - **Remote testing:** See `docs/testing/remote.md` for complete guide on testing the remote server (OAuth, web UI, CLI client) ## Development Notes ### Automated Code Review 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. ### Contributor Documentation 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.