OpenTelemetry MCP — Installieren & Live-Demo

Warum nutzen

Hauptfunktionen

Unified MCP for querying OpenTelemetry traces across Jaeger, Tempo, Datadog, and other backends.
Maintained by traceloop (community)
Written in Python
188+ GitHub stars at last check
Open source on GitHub

Live-Demo

In der Praxis

opentelemetry-mcp-server.replay ▶ bereit

0/0

Installieren

Wählen Sie Ihren Client

~/Library/Application Support/Claude/claude_desktop_config.json · Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "opentelemetry-mcp-server": {
      "command": "TODO",
      "args": [
        "See README: https://github.com/traceloop/opentelemetry-mcp-server"
      ]
    }
  }
}

Öffne Claude Desktop → Settings → Developer → Edit Config. Nach dem Speichern neu starten.

~/.cursor/mcp.json · .cursor/mcp.json

{
  "mcpServers": {
    "opentelemetry-mcp-server": {
      "command": "TODO",
      "args": [
        "See README: https://github.com/traceloop/opentelemetry-mcp-server"
      ]
    }
  }
}

Cursor nutzt das gleiche mcpServers-Schema wie Claude Desktop. Projektkonfiguration schlägt die globale.

VS Code → Cline → MCP Servers → Edit

{
  "mcpServers": {
    "opentelemetry-mcp-server": {
      "command": "TODO",
      "args": [
        "See README: https://github.com/traceloop/opentelemetry-mcp-server"
      ]
    }
  }
}

Klicken Sie auf das MCP-Servers-Symbol in der Cline-Seitenleiste, dann "Edit Configuration".

~/.codeium/windsurf/mcp_config.json

{
  "mcpServers": {
    "opentelemetry-mcp-server": {
      "command": "TODO",
      "args": [
        "See README: https://github.com/traceloop/opentelemetry-mcp-server"
      ]
    }
  }
}

Gleiche Struktur wie Claude Desktop. Windsurf neu starten zum Übernehmen.

~/.continue/config.json

{
  "mcpServers": [
    {
      "name": "opentelemetry-mcp-server",
      "command": "TODO",
      "args": [
        "See README: https://github.com/traceloop/opentelemetry-mcp-server"
      ]
    }
  ]
}

Continue nutzt ein Array von Serverobjekten statt einer Map.

~/.config/zed/settings.json

{
  "context_servers": {
    "opentelemetry-mcp-server": {
      "command": {
        "path": "TODO",
        "args": [
          "See README: https://github.com/traceloop/opentelemetry-mcp-server"
        ]
      }
    }
  }
}

In context_servers hinzufügen. Zed lädt beim Speichern neu.

claude mcp add opentelemetry-mcp-server -- TODO 'See README: https://github.com/traceloop/opentelemetry-mcp-server'

Einzeiler. Prüfen mit claude mcp list. Entfernen mit claude mcp remove.

Anwendungsfälle

Praxisnahe Nutzung: OpenTelemetry MCP

Use OpenTelemetry MCP for its primary workflow

👤 Developers using AI coding agents ⏱ ~10 min beginner

Wann einsetzen: You need the capability: Unified MCP for querying OpenTelemetry traces across Jaeger, Tempo, Datadog, and other backends.

Voraussetzungen

MCP server installed — See https://github.com/traceloop/opentelemetry-mcp-server for install instructions

Ablauf

Install

Install OpenTelemetry MCP following the README at https://github.com/traceloop/opentelemetry-mcp-server✓ Kopiert

→ MCP server appears in your client's available tools/skills
Invoke

Use OpenTelemetry MCP to complete the task described in its docs.✓ Kopiert

→ Agent calls the relevant tool/skill and returns a result

Ergebnis: Working integration with the capabilities advertised by the project.

Fallstricke

README is the source of truth; details here may lag upstream — Check https://github.com/traceloop/opentelemetry-mcp-server for the latest setup steps and tool list

Mehr

Ressourcen

📖 Offizielle README auf GitHub lesen

🐙 Offene Issues ansehen

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