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MCP Datadog Server

@ClaudioLazaro

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基本情報

カテゴリ

開発者ツール

トランスポート

stdio

作者

ClaudioLazaro

投稿者

Claudio Lazaro

MCP Datadog Server について

MCP Datadog Server

#mcp-datadog#datadog-server#api-integration

MCP Datadog Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "datadog": {
      "command": "mcp-datadog-server",
      "args": [
        "serve"
      ],
      "env": {
        "DD_API_KEY": "your_api_key",
        "DD_APP_KEY": "your_app_key",
        "DD_SITE": "datadoghq.com"
      }
    }
  }
}

MCP Datadog Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Mcp Datadog Server?

Mcp Datadog Server is a production‑ready MCP (Model Context Protocol) server that provides 351 tools for interacting with Datadog APIs through LLMs. It includes curated tools, CRUD operations for core resources, and automatically generated tools from the official Datadog schema. It is designed for developers and SRE teams who want to manage Datadog resources using natural language.

How to use Mcp Datadog Server?

Install globally via npm (npm install -g mcp-datadog-server) or clone the repository and run npm install. Set the required environment variables DD_API_KEY and DD_APP_KEY (plus optional DD_SITE, etc.). Start the server with mcp-datadog-server serve or integrate it with LLMs like Claude Desktop by adding an MCP server entry in the configuration file.

Key features of Mcp Datadog Server

  • 351 tools total: 9 curated, 25 CRUD, 319 generated from schema
  • Automatic parameter discovery by LLMs via JSON Schema
  • Robust validation with Zod schemas
  • Progress tracking and intelligent error handling with retry
  • Rich CLI for tool listing, inspection, and validation

Use cases of Mcp Datadog Server

  • Create, update, and delete Datadog monitors using natural language
  • Manage dashboards, downtimes, users, and teams via LLM conversations
  • Search logs and query metrics with complex filters
  • Handle incidents and synthetic tests through automated tool calls
  • Filter tool categories to focus on specific Datadog resources (e.g., Dashboards, Logs)

よくある質問

1

How does the LLM discover tool parameters?

The LLM automatically lists all available tools, fetches each tool’s full JSON Schema, and constructs valid calls with the correct parameter names, types, and constraints – without needing prior knowledge of the parameters.

2

What environment variables are required and optional?

Required: `DD_API_KEY` (Datadog API key) and `DD_APP_KEY` (Datadog application key). Optional: `DD_SITE` (default `datadoghq.com`), `DD_SUBDOMAIN`, `MCP_DD_FOLDERS` (filter categories), `MCP_DD_SCHEMA_PATH`, `MCP_DD_MAX_RETRIES`, `MCP_DD_RETRY_BASE_MS`, `MCP_DD_TIMEOUT_MS`, and `MCP_DD_USER_AGENT`.

3

How can I filter which tools are loaded?

Set the environment variable `MCP_DD_FOLDERS` to a comma‑separated list of categories (e.g., `Dashboards,Monitors,Logs`) to load only tools from those categories. You can also use the `--folders` flag when starting the server.

4

What rate limiting handling is included?

The server automatically respects Datadog’s `retry-after` headers and uses configurable retry logic (`MCP_DD_MAX_RETRIES` and `MCP_DD_RETRY_BASE_MS`) to handle rate limits gracefully.

5

How do I debug “Tool not found” or “Invalid API key” errors?

Use `mcp-datadog-server list-tools --detailed | grep <tool_name>` to check if the tool exists. Validate credentials with `mcp-datadog-server validate`. Ensure `DD_API_KEY` and `DD_APP_KEY` are set correctly in your environment.

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