Sentry - OpenClaw Skill — OpenClaw Tutorials

Install Command

npx clawhub@latest install sentry

Installation Guide

Check Environment

Make sure Node.js 22+ and OpenClaw are installed. Run openclaw --version in your terminal to verify.

Run Installation

Run the install command above in your terminal. ClawHub will automatically download and install Sentry to the ~/.openclaw/skills/ directory.

Verify Installation

Run openclaw skills list to check your installed skills and confirm Sentry appears in the list.

Configure (Optional)

Follow the configuration instructions in the description below to add skill settings to ~/.config/openclaw/openclaw.json5.

Manual Installation: Copy the Skill folder to ~/.openclaw/skills/ or the skills/ directory in your project root. Make sure the folder contains a SKILL.md file.

Issue list querying and filtering Error stack trace and event detail analysis AI automated root cause diagnosis

Detailed Description

Sentry MCP server brings the capabilities of the Sentry error monitoring platform into the AI assistant, enabling direct querying and analysis of errors and performance issues in production environments, combined with AI-generated fix suggestions.

Core Features

Issue Query (list_issues): List error issues in a project, with filtering and sorting by status, priority, and time range
Issue Details (get_issue): Get complete information for a single issue, including error message, affected user count, and first/last occurrence times
Event Analysis (get_event): View stack traces, request parameters, user info, and device environment for specific error events
AI Diagnosis (get_autofix): Call Sentry's AI Autofix feature to automatically analyze root causes and generate fix suggestions
Organization Management: List accessible organizations and projects, manage teams and permissions

Configuration

{
  "mcpServers": {
    "sentry": {
      "command": "npx",
      "args": ["-y", "@sentry/mcp-server"],
      "env": {
        "SENTRY_AUTH_TOKEN": "sntrys_your-token"  // Get from Sentry settings page
      }
    }
  }
}

Use Cases

On-call response: Quickly view the latest production errors and their impact scope
Bug fixing: Get error stack traces and context, let AI directly locate code issues
Trend analysis: Analyze error frequency changes to identify regression issues
Auto-fix: Generate fix code directly based on AI diagnostic results

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