Set Up the Datadog MCP Server

Docs > Bits AI > Datadog MCP Server > Set Up the Datadog MCP Server

Learn how to set up and configure the Datadog MCP Server, which lets you retrieve telemetry insights and manage platform features directly from AI-powered clients. Select your client:

Datadog’s Cursor and VS Code extension includes built-in access to the managed Datadog MCP Server.

Install the extension (omit --profile and profile name to install to the default Cursor profile):
```
cursor --install-extension datadog.datadog-vscode --profile <PROFILE_NAME>
```
Alternatively, install the Datadog extension. If you have the extension installed already, make sure it’s the latest version.
Sign in to your Datadog account.
Restart the IDE.
Confirm the Datadog MCP Server is available and the tools are listed: Go to Cursor Settings (Shift + Cmd/Ctrl + J), select the Tools & MCP tab, and expand the extension’s tools list.
If you previously installed the Datadog MCP Server manually, remove it from the IDE’s configuration to avoid conflicts.

Point your AI agent to the MCP Server endpoint for your regional Datadog site. For the correct instructions, use the Datadog Site selector on the right side of this documentation page to select your site.

Selected endpoint (): .

Run in terminal:

claude mcp add --transport http datadog-mcp

Alternatively, add to ~/.claude.json:

{
   "mcpServers": {
     "datadog": {
       "type": "http",
       "url": ""
      }
    }
 }

To enable product-specific tools, include the toolsets query parameter at the end of the endpoint URL. For example, this URL enables only APM and LLM Observability tools:
```
?toolsets=apm,llmobs
```

If remote authentication is not available, use local binary authentication instead.

Connect Claude (including Claude Cowork) to the Datadog MCP Server by adding it as a custom connector with the remote MCP URL.

Follow the Claude help center guide on custom connectors to add a new custom connector.
When prompted for a URL, enter the Datadog MCP Server endpoint for your Datadog site (). For the correct instructions, use the Datadog Site selector on the right side of this documentation page to select your site.
To enable product-specific tools, include the toolsets query parameter at the end of the endpoint URL. For example, this URL enables only APM and LLM Observability tools:
```
?toolsets=apm,llmobs
```
Complete the OAuth login flow when prompted.

Selected endpoint (): .

Edit ~/.codex/config.toml (or your Codex CLI configuration file) to add the Datadog MCP Server with HTTP transport and the endpoint URL for your site. For example:
```
[mcp_servers.datadog]
url = ""
```
To enable product-specific tools, include the toolsets query parameter at the end of the endpoint URL. For example, this URL enables only APM and LLM Observability tools:
```
?toolsets=apm,llmobs
```
Log in to the Datadog MCP Server:
```
codex mcp login datadog
```
This opens your browser to complete the OAuth flow. Codex stores the resulting credentials so you don’t need to log in again until the token expires.

Datadog’s Cursor and VS Code extension includes built-in access to the managed Datadog MCP Server.

Install the extension (omit --profile and profile name to install to the default VS Code profile):
```
code --install-extension datadog.datadog-vscode --profile <PROFILE_NAME>
```
Alternatively, install the Datadog extension. If you have the extension installed already, make sure it’s the latest version.
Sign in to your Datadog account.
Restart the IDE.
Confirm the Datadog MCP Server is available and the tools are listed: Open the chat panel, select agent mode, and click the Configure Tools button.
If you previously installed the Datadog MCP Server manually, remove it from the IDE’s configuration to avoid conflicts. Open the command palette (Shift + Cmd/Ctrl + P) and run MCP: Open User Configuration.

JetBrains offers the Junie and AI Assistant plugins for their range of IDEs. Alternatively, many developers use an agent CLI, such as Claude Code or Codex, alongside their IDE.

Point your plugin to the MCP Server endpoint for your regional Datadog site. For the correct instructions, use the Datadog Site selector on the right side of this documentation page to select your site.

Selected endpoint (): .

Junie

Go to Tools > Junie > MCP Settings and add the following block:

{
  "mcpServers": {
    "datadog": {
      "type": "http",
      "url": ""
    }
  }
}

To enable product-specific tools, include the toolsets query parameter at the end of the endpoint URL. For example, this URL enables only APM and LLM Observability tools:

?toolsets=apm,llmobs

You are prompted to login through OAuth. The status indicator in the settings displays a green tick when the connection is successful.

JetBrains AI Assistant

Go to Tools > AI Assistant > Model Context Protocol (MCP) and add the following block:

{
  "mcpServers": {
    "datadog": {
      "url": ""
      "headers": {
        "DD_API_KEY": "<YOUR_API_KEY>",
        "DD_APPLICATION_KEY": "<YOUR_APP_KEY>"
      }
    }
  }
}

To enable product-specific tools, include the toolsets query parameter at the end of the endpoint URL. For example, this URL enables only APM and LLM Observability tools:

?toolsets=apm,llmobs

The status indicator in the settings displays a green tick when the connection is successful.

Agent CLIs

Many developers use an agent CLI such as Claude Code or Codex alongside their JetBrains IDE. See the configuration for those CLI tools:

The Datadog plugin for JetBrains IDEs integrates with these agent CLIs. For an uninterrupted experience, install the plugin at the same time as you configure the Datadog MCP Server.

For most other supported clients, use these instructions for remote authentication. For Cline or when remote authentication is unreliable or not available, use local binary authentication.

Selected endpoint (): .

Add the Datadog MCP Server to your client’s configuration file using the HTTP transport and your site’s endpoint URL. For example:
```
{
   "mcpServers": {
     "datadog": {
       "type": "http",
       "url": ""
     }
   }
 }
```
To enable product-specific tools, include the toolsets query parameter at the end of the endpoint URL. For example, this URL enables only APM and LLM Observability tools:
```
?toolsets=apm,llmobs
```

Example configuration file locations:

Client	Configuration file
Gemini CLI	`~/.gemini/settings.json`
Kiro CLI	`~/.kiro/settings/mcp.json`

Supported clients

Client	Developer	Notes
Cursor	Cursor	Datadog Cursor & VS Code extension recommended.
Claude Code	Anthropic
Claude	Anthropic	Use custom connector setup. Includes Claude Cowork.
Codex CLI	OpenAI
VS Code	Microsoft	Datadog Cursor & VS Code extension recommended.
JetBrains IDEs	JetBrains	Datadog plugin recommended.
Goose, Kiro, Kiro CLI, Cline	Various	See the Other tab above. Use local binary authentication for Cline if remote authentication is unreliable.

The Datadog MCP Server is under significant development, and additional supported clients may become available.

Authentication

The MCP Server uses OAuth 2.0 for authentication. If you cannot go through the OAuth flow (for example, on a server), you can provide a Datadog API key and application key as DD_API_KEY and DD_APPLICATION_KEY HTTP headers.

For example, based on your selected Datadog site ():

{
  "mcpServers": {
    "datadog": {
      "type": "http",
      "url": "",
      "headers": {
          "DD_API_KEY": "<YOUR_API_KEY>",
          "DD_APPLICATION_KEY": "<YOUR_APPLICATION_KEY>"
      }
    }
  }
}

For security, use a scoped API key and application key from a service account that has only the required permissions.

Local binary authentication

Local authentication is recommended for Cline and when remote authentication is unreliable or not available. After installation, you typically do not need to update the local binary to benefit from MCP Server updates, as the tools are remote.

Set up Datadog MCP Server local binary

Install the Datadog MCP Server binary (macOS and Linux):
```
curl -sSL https://coterm.datadoghq.com/mcp-cli/install.sh | bash
```
This installs the binary to ~/.local/bin/datadog_mcp_cli.
For Windows, download the Windows version.
Run datadog_mcp_cli login manually to walk through the OAuth login flow and choose a Datadog site.
Configure your AI client to use the stdio transport with datadog_mcp_cli as the command. For example (replace <USERNAME> with your username):
```
{
  "mcpServers": {
    "datadog": {
      "type": "stdio",
      "command": "/Users/<USERNAME>/.local/bin/datadog_mcp_cli",
      "args": [],
      "env": {}
    }
  }
}
```
On Windows, replace the command path with the location of the downloaded .exe file (for example, C:\Users\<USERNAME>\bin\datadog_mcp_cli.exe).
For Claude Code, you can instead run:
```
claude mcp add datadog --scope user -- ~/.local/bin/datadog_mcp_cli
```

Test access to the MCP Server

Install the MCP inspector, a developer tool for testing and debugging MCP servers.
```
npx @modelcontextprotocol/inspector
```
In the inspector’s web UI, for Transport Type, select Streamable HTTP.
For URL, enter the MCP Server endpoint for your regional Datadog site.
For example, for :
Click Connect, then go to Tools > List Tools.
Check if the available tools appear.