toolkit
getsentry · getsentry/toolkit
Provides agentic tooling as an MCP server and Claude plugin to integrate Sentry's error monitoring and performance debugging features into coding agents.
Agentic tooling for Sentry
Preview
What you can do with it
- Ask Claude Code to investigate a recent Sentry error and suggest potential fixes in your codebase.
- Use the agent to get a summary of new issues in Sentry related to a recent deployment.
- Have the agent check Sentry performance traces for bottlenecks in your application.
Safety check
Usable, but read the notes first.
- ●No clear license: check with the author before using it in a commercial product.
Automated scan of the repo files. Always review code you run.
From the README
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.
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:
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
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_errors, search_traces, search_logs, 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:
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.
Seer is not part of self-hosted Sentry, so the seer skill is left out of the
default skill set whenever --host points at a non-sentry.io host. If your
self-hosted deployment does run Seer, opt back in explicitly:
npx @sentry/mcp-server@latest --access-token=TOKEN --host=sentry.example.com --skills=inspect,seer
You can also disable any other skill to prevent unsupported tools from being exposed:
npx @sentry/mcp-server@latest --access-token=TOKEN --host=sentry.example.com --disable-skills=project-management
For self-hosted instances without TLS:
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:
{
"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
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-5.6-luna'
OPENROUTER_REASONING_EFFORT= # Optional OpenRouter reasoning effort, defaults to 'high'
# Optional overrides
SENTRY_HOST= # For self-hosted deployments (drops 'seer' from the default skills)
MCP_SKILLS= # Grant specific skills (comma-separated, e.g. 'inspect,seer')
MCP_DISABLE_SKILLS= # Disable specific skills (comma-separated, e.g. 'project-management')
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 for detailed configuration options.
Example MCP Configuration
{
"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.
Setting SENTRY_HOST to a self-hosted host also drops the seer skill from
the default set, since Seer is not available on self-hosted Sentry. For a
self-hosted deployment that does run Seer, opt in with `MCP