Yes, Metricwatch is free to use.

How do I install Metricwatch?

Metricwatch is a local plugin. Install it using npm package: @reneturcios/metricwatch and add the generated configuration snippet to your AI app's MCP config file. Then restart your AI app.

Is Metricwatch safe to use?

Metricwatch scored 6.2/10 (moderate risk) in MCP Marketplace's automated security scan. It has 2 high or critical findings to review. It's listed, but review the security report on this page before installing.

What credentials does Metricwatch need?

Metricwatch requires the following credentials or environment variables: DATADOG_API_KEY, DATADOG_APP_KEY. You can find setup instructions on the server detail page.

What AI apps work with Metricwatch?

Metricwatch uses the Model Context Protocol (MCP) and works with any MCP-compatible AI app, including Claude, ChatGPT / Codex, Gemini, Copilot, Cursor, and more.

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Metricwatch MCP Server

by CloudCorpRecords

Developer ToolsModerate6.2MCP RegistryLocal

Free

Server data from the Official MCP Registry

Datadog metrics, dashboards, logs, incidents, and monitors from your MCP client.

About

Datadog metrics, dashboards, logs, incidents, and monitors from your MCP client.

Security Report

6.2

Moderate6.2Moderate Risk

metricwatch is a read-only Datadog client that requires both an API key and an application key from environment variables, sends them only as DD-API-KEY and DD-APPLICATION-KEY headers to the official api.<site> host, and exposes only GET/search operations. Its permissions match its stated purpose, and the code shows no exfiltration, shell execution, hardcoded secrets, or obfuscation; only minor observations remain, such as the lack of an explicit site allowlist and the broad log/monitor data it can return. Supply chain analysis found 4 known vulnerabilities in dependencies (0 critical, 2 high severity). Package verification found 1 issue.

8 files analyzed · 8 issues found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

HTTP Network Access

Connects to external APIs or services over the internet.

env_vars

Check that this permission is expected for this type of plugin.

system_info

Check that this permission is expected for this type of plugin.

What You'll Need

Set these up before or after installing:

DATADOG_API_KEYRequired

DATADOG_APP_KEYRequired

How to Install

Add this to your MCP configuration file:

{
  "mcpServers": {
    "io-github-cloudcorprecords-metricwatch": {
      "env": {
        "DATADOG_API_KEY": "your-datadog-api-key-here",
        "DATADOG_APP_KEY": "your-datadog-app-key-here"
      },
      "args": [
        "-y",
        "@reneturcios/metricwatch"
      ],
      "command": "npx"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

metricwatch

metricwatch gives an MCP client or a terminal read access to a Datadog account: metric timeseries queries and metric metadata, dashboards, log search, incidents, monitors, and downtimes. It is a clean-room rebuild of the Datadog MCP tool surface from Datadog's public API documentation, covering the read core listed below.

Two credentials are required, because the Datadog API requires both on every call: an API key in DATADOG_API_KEY and an application key in DATADOG_APP_KEY. They are sent as the DD-API-KEY and DD-APPLICATION-KEY headers and never appear in output. Set DATADOG_SITE (for example datadoghq.eu) to target a different Datadog site; the default is datadoghq.com and calls go to https://api.<site>. When either key is missing, every call fails with an error that names the missing variable.

Install

npx @reneturcios/metricwatch list_metrics

Or run the container image:

docker run -i -e DATADOG_API_KEY -e DATADOG_APP_KEY ghcr.io/cloudcorprecords/metricwatch

The container defaults to the MCP server (see below). Pass CLI arguments to use it as a CLI instead.

CLI

Every MCP tool is also a CLI subcommand. Tool arguments are passed as one JSON object with --json:

export DATADOG_API_KEY=<redacted>
export DATADOG_APP_KEY=<redacted>

metricwatch query_timeseries --json '{"from": 1700000000, "to": 1700003600, "query": "avg:system.cpu.user{*}"}'
metricwatch list_metrics --json '{"limit": 20}'
metricwatch get_dashboard --json '{"dashboard_id": "abc-123"}'
metricwatch search_logs --json '{"query": "service:web status:error", "limit": 25}'
metricwatch list_monitors
metricwatch get_monitor --json '{"monitor_id": 42}'

metricwatch --version

Results print as JSON. Exit codes: 0 on success, 1 when an API call fails (including a missing key), 2 for usage errors.

MCP server

One bin serves both faces. The mcp subcommand starts a stdio MCP server:

npx -y @reneturcios/metricwatch mcp

MCP client configuration:

{
  "mcpServers": {
    "metricwatch": {
      "command": "npx",
      "args": ["-y", "@reneturcios/metricwatch", "mcp"],
      "env": {
        "DATADOG_API_KEY": "your Datadog API key",
        "DATADOG_APP_KEY": "your Datadog application key"
      }
    }
  }
}

Tools

Tool	Input (required in bold)	What it does
`query_timeseries`	`from`, `to`, `query`	Queries a metric timeseries (v1 query endpoint).
`list_metrics`	`from`, `limit`	Lists metric names in the account.
`get_metric_metadata`	`metric_name`	Returns one metric's type, unit, and description.
`list_dashboards`	`limit`	Lists dashboards.
`get_dashboard`	`dashboard_id`	Returns one dashboard with its widgets.
`search_logs`	`query`, `from`, `to`, `limit`	Searches log events (v2 logs search).
`list_incidents`	`limit`	Lists incidents.
`get_incident`	`incident_id`	Returns one incident.
`list_monitors`	`name`, `limit`	Lists monitors, optionally name-filtered.
`get_monitor`	`monitor_id`	Returns one monitor by integer id.
`list_downtimes`	`current_only`	Lists downtimes (monitor silences).

Out of scope for this read core: APM trace/span detail, synthetics, RUM, notebooks, SLO administration, event writes, incident creation or mutation, and on-call — see BUILD-REPORT.md.

Development

npm install
npm run build   # tsc -> dist/
npm test        # node test runner over test/*.test.ts, no network (fake fetch fixtures)
npm run dev     # run the CLI from source via tsx

License

MIT — see LICENSE.

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