A fast, lightweight [MCP](https://modelcontextprotocol.io/) server for Sentry, written in Rust.
A fast, lightweight MCP server for Sentry, written in Rust. That is what the sentry mcp rs mcp server brings to an AI assistant: the same capability, reachable through the Model Context Protocol rather than a separate app or dashboard.
The server publishes 3 tools. What each one is for:
get_issue_details — Retrieve detailed information about a specific Sentry issueget_trace_details — The get_trace_details tool exposed by this serversearch_issue_events — The search_issue_events tool exposed by this serverInstallation goes through your MCP client rather than a global install: point it at @modelcontextprotocol/inspector on npm and it is fetched when the client starts. The copy-paste blocks for Claude Desktop, Claude Code and Cursor are further down this page.
Configuration is passed through the environment: SENTRY_AUTH_TOKEN, SENTRY_HOST. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.
Plenty of monitoring and observability servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Sentry MCP Rs's toolset — get_issue_details, get_trace_details, search_issue_events — is a fair guide to whether it matches your workflow. It is maintained by utapyngo; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
| Tool | What it does |
|---|---|
| get_issue_details | Retrieve detailed information about a specific Sentry issue. |
| get_trace_details | The get_trace_details tool exposed by this server. |
| search_issue_events | The search_issue_events tool exposed by this server. |
Or without installation using mise:
```json
{
"mcpServers": {
"sentry": {
"command": "mise",
"args": ["x", "github:utapyngo/sentry-mcp-rs", "--", "sentry-mcp"],
"env": {
"SENTRY_AUTH_TOKEN": "your_token_here",
"SENTRY_HOST": "sentry.io"
}
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| SENTRY_AUTH_TOKEN | Credential the server authenticates with. | Yes |
| SENTRY_HOST | Endpoint or connection string the server talks to. | Optional |
Give your coding agent the full DevTools toolbox: traces, network, console, heap snapshots and Lighthouse.
Dashboards, Prometheus and Loki queries, incidents and alerts — observability by conversation.
Errors with full context — stack traces, issue triage and AI-powered root-cause analysis from Sentry's server.
Enables enhanced web research capabilities for large language models through intelligent search queuing and advanced content extraction.
Automates browser interactions and enables Large Language Models (LLMs) to interact with web pages through Playwright and Chrome DevTools Protocol
Guides tool usage by providing recommendations for MCP tools at each problem-solving stage.