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MCP Datadog Server

@ClaudioLazaro

基本信息

分类

开发工具

传输方式

stdio

作者

ClaudioLazaro

提交者

Claudio Lazaro

关于 MCP Datadog Server

MCP Datadog Server

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

MCP Datadog Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "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 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

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)

常见问题

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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