Enables AI models to query and analyze error reports and events from Sentry.
Most monitoring and observability work still happens through a UI a human drives. Sentry Integration MCP server moves it into the conversation instead. Enables AI models to query and analyze error reports and events from Sentry.
This is a Model Context Protocol (MCP) server implemented in TypeScript for connecting to the Sentry error tracking service. This server allows AI models to query and analyze error reports and events on Sentry.
@modelcontextprotocol/inspector on npm is all you need. Most clients run it directly, so configuration is a few lines and a restart.
The server publishes 2 tools. What each one is for:
Input — * issue_id_or_url (string): Sentry issue ID or URL to analyzeReturns — Issue details including:Configuration is passed through the environment: SENTRY_AUTH_TOKEN, SENTRY_BASE_URL. 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 Integration's toolset — Input, Returns — is a fair guide to whether it matches your workflow. It is maintained by Zzzccs123; 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 |
|---|---|
| Input | * issue_id_or_url (string): Sentry issue ID or URL to analyze |
| Returns | Issue details including: |
{
"mcpServers": {
"sentry-integration": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/inspector"],
"env": {
"SENTRY_AUTH_TOKEN": "your-value",
"SENTRY_BASE_URL": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
| Variable | Description | Required |
|---|---|---|
| SENTRY_AUTH_TOKEN | Credential the server authenticates with. | Yes |
| SENTRY_BASE_URL | Endpoint or connection string the server talks to. | Yes |
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.