Sentry Server
FreeNot checkedEnables searching and analyzing Sentry issues, events, and traces via natural language, providing tools for error investigation and distributed tracing.
About
Enables searching and analyzing Sentry issues, events, and traces via natural language, providing tools for error investigation and distributed tracing.
README
Forked from elad12390/loki-mcp — retargeted from Grafana Loki to Sentry. Same "few sharp tools, no config" ergonomics, new backend. This repo keeps the original's git history.
An MCP server to easily search and analyze Sentry issues, events, and traces — without writing Sentry queries or clicking through the UI.
This is a focused, fast alternative to the official Sentry MCP: a small, predictable tool set modeled on a battle-tested log-search MCP, talking directly to the Sentry REST API.
Quick Start
You can run this server directly using npx:
export SENTRY_AUTH_TOKEN="sntryu_..." # Sentry auth token (see Configuration)
export SENTRY_URL="https://us.sentry.io" # your region/host (default: https://sentry.io)
export SENTRY_ORG="my-org" # optional; auto-detected if omitted
npx @elad12390/sentry-mcp
Features
This MCP server provides 4 tools, 3 resources, and 3 prompts. AI assistants automatically understand when to use each based on natural language.
Tools
🔍 sentry_search_issues — Your primary search tool
- Just say: "check sentry", "what's breaking", "show me errors", "unresolved issues", "top errors", "how many errors"
- Searches grouped issues across ALL projects automatically (or filter by
project) - Uses Sentry search syntax in
query(is:unresolved level:error,release:latest, free text) - Set
count=truefor event counts + an ASCII trend chart instead of the issue list
🔗 sentry_trace_lookup — Distributed tracing
- Just say: "follow this trace", "what happened in this request", "trace this id across services"
- Returns every span and error in a trace, grouped by service, as a timeline
🔎 sentry_get_issue_details — Root cause analysis
- Just say: "show the stack trace", "what happened before this error", "why did this fail"
- Returns the exception + stack trace, the breadcrumbs (what happened right before), request context, tags, and the trace ID
🧩 sentry_pattern_analysis — Group & rank error patterns
- Just say: "group similar errors", "what error types", "do we have one problem or many"
- Ranks issue groups by event volume and merges near-duplicate titles into higher-level patterns
Resources (Read-only Data)
sentry://projects — List all projects in the org
- Read this first to know what you can filter by
sentry://tags — List all tag keys (searchable metadata)
- Shows what you can filter by (environment, release, browser, etc.)
sentry://tags/{key}/values — Get values for a specific tag
- Example:
sentry://tags/environment/values
Prompts (Guided Workflows)
debug-error — Search the issue, pull stack trace + breadcrumbs, gauge blast radius
- Arguments:
error_text(required),project,time_window
trace-request — Follow a trace ID across services
- Arguments:
trace_id(required),time_window
health-check — List projects, count errors + trend, find dominant patterns
- Arguments:
project,time_window
Usage Tips for AI Assistants
When the user says "check sentry" or "what's broken", you should:
- Read
sentry://projectsif you don't know what projects exist - Use
sentry_search_issuesas your primary tool — it works across all projects - Follow up with
sentry_get_issue_detailson an interesting issue for the stack trace + breadcrumbs - Use
sentry_search_issueswithcount=truewhen they ask "how many" / "is it getting worse" - Use
sentry_pattern_analysisduring incidents to see if it's one problem or many
For complex debugging, use the prompts: debug-error, trace-request, health-check.
Example Conversations
User: "Check sentry for errors in the python-fastapi project"
AI: Uses sentry_search_issues with project="python-fastapi", query="is:unresolved"
User: "How many errors happened today?"
AI: Uses sentry_search_issues with count=true, time_window="24h"
User: "Why is PYTHON-FASTAPI-TK failing?"
AI: Uses sentry_get_issue_details with the issue id
User: "Follow trace ce8f0d3961214198a040517b3dfda0d4"
AI: Uses sentry_trace_lookup
Configuration
Set the following environment variables:
SENTRY_AUTH_TOKEN(required): A Sentry auth token. Create one at Settings → Auth Tokens (organization token) or User Settings → Personal Tokens. Required scopes:org:read,project:read,event:read.SENTRY_URL: Base URL of your Sentry instance. Defaulthttps://sentry.io. SaaS users on a specific region should usehttps://us.sentry.io,https://de.sentry.io, etc. Self-hosted: your own host.SENTRY_ORG: Organization slug. Optional — if omitted, the first org the token can access is auto-detected.SENTRY_PROJECT: Default project slug used for tag-value lookups. Optional — defaults to the first project in the org.
Development
bun install
bun run build
bun test
See AGENTS.md for code style and contribution notes.
Install Sentry Server in Claude Desktop, Claude Code & Cursor
unyly install sentry-mcp-serverInstalls into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.
First time? Get the CLI: curl -fsSL https://unyly.org/install | sh
Or configure manually
Run in your terminal:
claude mcp add sentry-mcp-server -- npx -y github:elad12390/sentry-mcpFAQ
Is Sentry Server MCP free?
Yes, Sentry Server MCP is free — one-click install via Unyly at no cost.
Does Sentry Server need an API key?
No, Sentry Server runs without API keys or environment variables.
Is Sentry Server hosted or self-hosted?
A hosted option is available: Unyly runs the server in the cloud, no local setup required.
How do I install Sentry Server in Claude Desktop, Claude Code or Cursor?
Open Sentry Server on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
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