Sentry & Datadog APM Observability MCP Profile

AI-generated MCP configuration example referring to Sentry and Datadog. Verify that the named servers exist and provide the requested API capabilities.

Tags: mcp, sentry, datadog, observability, apm, logs, error-tracking

Category: devops

Listing attribution: SimplyUtils

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Sentry & Datadog APM Observability MCP Profile

Overview

Connect your AI agent directly to Sentry issue tracking and Datadog APM logs using this MCP server profile. Agents can pull production unhandled exception traces, correlate error frequencies with recent releases, and suggest immediate code patches.

MCP Configuration (mcp_config.json)

{
  "mcpServers": {
    "sentry-observability": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-sentry"],
      "env": {
        "SENTRY_AUTH_TOKEN": "sntrys_your_read_only_token",
        "SENTRY_ORG": "your-org-slug"
      }
    },
    "datadog-logs": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-datadog"],
      "env": {
        "DATADOG_API_KEY": "your_dd_api_key",
        "DATADOG_APP_KEY": "your_dd_app_key",
        "DATADOG_SITE": "datadoghq.com"
      }
    }
  }
}

Recommended Diagnostic Workflow

1. Fetch latest high-impact production issue from Sentry: sentry_get_latest_issues({ limit: 5 }).

2. Inspect exact stack trace lines and affected file paths.

3. Locate corresponding source file in repository.

4. Draft root cause analysis and propose fix.