Datadog MCP | Api Key Datadog connector for AI agents

Tools your monitoring agent reaches for on Datadog, scoped per user.

CALL ANY TOOL

Query metrics, list monitors and incidents, search logs, and surface events from across your stack.

datadog_metrics_query

Query metrics

Query time-series metrics with a Datadog formula and optional rollup.

Parameters

Name

Type

Required

Description

query

string

Required

Datadog metrics query string

from_time

integer

Required

Start time as Unix epoch

to_time

integer

Required

End time as Unix epoch

datadog_monitors_list

List monitors

datadog_monitor_get

Get monitor

datadog_events_list

List events

datadog_incidents_list

List incidents

datadog_logs_search

Search logs

Build your Agent

Drop the toolkit in, point it at the user, and your monitoring agent can use Datadog from the first run.

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import { ScalekitClient } from "@scalekit-sdk/node";
import { DynamicStructuredTool } from "@langchain/core/tools";
import { createReactAgent } from "@langchain/langgraph/prebuilt";
import { z } from "zod";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["datadog"], toolNames: ["datadog_metrics_query", "datadog_monitors_list", "datadog_monitor_get"] },
  pageSize: 100,
});

const lcTools = tools.map((t) => new DynamicStructuredTool({
  name: t.tool.definition.name,
  description: t.tool.definition.description,
  schema: z.object({}).passthrough(),
  func: async (args) => {
    const { data } = await sk.tools.executeTool({
      toolName: t.tool.definition.name,
      identifier: "user_123",
      params: args,
    });
    return JSON.stringify(data);
  },
}));

const agent = createReactAgent({ llm, tools: lcTools });

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import { ScalekitClient } from "@scalekit-sdk/node";
import OpenAI from "openai";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);
const openai = new OpenAI();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["datadog"], toolNames: ["datadog_metrics_query", "datadog_monitors_list", "datadog_monitor_get"] },
  pageSize: 100,
});

const llmTools = tools.map((t) => ({
  type: "function",
  function: {
    name: t.tool.definition.name,
    description: t.tool.definition.description,
    parameters: t.tool.definition.input_schema,
  },
}));

const resp = await openai.responses.create({
  model: "gpt-4o", input: prompt, tools: llmTools,
});

import { ScalekitClient } from "@scalekit-sdk/node";
import Anthropic from "@anthropic-ai/sdk";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);
const anthropic = new Anthropic();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["datadog"], toolNames: ["datadog_metrics_query", "datadog_monitors_list", "datadog_monitor_get"] },
  pageSize: 100,
});

const llmTools = tools.map((t) => ({
  name: t.tool.definition.name,
  description: t.tool.definition.description,
  input_schema: t.tool.definition.input_schema,
}));

const msg = await anthropic.messages.create({
  model: "claude-sonnet-4-6", max_tokens: 1024,
  tools: llmTools,
  messages: [{ role: "user", content: prompt }],
});

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import { Agent } from "@google/adk/agents";
import {
  MCPToolset, StreamableHTTPConnectionParams,
} from "@google/adk/tools/mcp";

const toolset = new MCPToolset({
  connectionParams: new StreamableHTTPConnectionParams({
    url: "https://mcp.scalekit.com/datadog",
    headers: { Authorization: `Bearer ${userScopedToken}` },
  }),
});

const agent = new Agent({
  name: "agent", model: "gemini-2.0-flash",
  tools: await toolset.getTools(),
});

Try these prompts

Paste any prompt into your agent to start using Datadog.

Search & recall

Copy the prompt

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List all monitors in ALERT state.

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Show me error-rate metrics for the last hour.

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Find monitors tagged with [service].

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Get the latest incident SEV-1 details.

Metrics & analysis

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Query p99 latency for [service] last 7 days.

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Show me request rate by endpoint today.

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Daily error count for [tag] this week.

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Compare CPU usage across [host group].

Incidents & logs

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List active incidents right now.

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Search logs for [error message] in last 30m.

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Which hosts triggered disk-usage alerts today?

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Show event stream for [service] last 2 hours.

SEE HOW AUTH WORKS

Users authorize Datadog once. Their credentials stay vaulted, every call is checked, and every action is logged.

Authorize

Your user connects

Datadog

once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access

Who:

user ‘A’

when:

Once per user

access:

Limited to user

Store

Their

Datadog

token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection

vault:

encrypted

scope:

per-user

tokens:

auto-refreshed

Resolve

When your agent calls a

Datadog

tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs

speed:

~40ms

check:

before every call

seen by:

nobody

Audit

Every

Datadog

tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it

history:

90 days

export:

SIEM-ready

logged:

every call

Test other agents

Same per-user auth pattern across other monitoring agents and MCP connectors. Working code, live demos, fork what fits.

ENGINEERING

DevOps assistant agent

Triage GitHub incidents, open Linear tickets, and notify the on-call channel in Slack with context already attached.

SUPPORT

Support triage agent

Read Zendesk tickets, fetch runbooks from Notion, and route to the right Slack channel with a drafted response.

Why Scalekit

Secure your agent's access. Connectors ship in minutes

Other connector libraries treat auth as a demo afterthought. Scalekit starts with user identity, scope enforcement, and audit.

01.

Metrics queried from the wrong org identity

A shared Datadog API key looks fine in a demo. In production, every metric query and log search is attributed to the service account. Org-level scope collapses. Scalekit resolves the user's key so queries run under the right identity.

// shared API key
key = "dd_api_shared_xxx"
audit → bot_service_account
org_filter → broken

// scalekit · per-user
key = resolve(user_id)
audit → user_abc
scope → enforced ✓

02.

Authentication is not authorization

03.

Multi-tenancy is architectural

04.

Datadog today. Others tomorrow.

“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”

Venu Madhav Kattagoni

Head of Engineering / Von

On this page

Tool and actions Framework Compatibility Starter Prompt Auth Lifecycle Try Other Agents Why Scalekit

Frequently Asked Questions

Does the agent access Datadog as the user or as a shared key?

As the user. Each workspace member authorizes once and Scalekit resolves their credential at request time. Audit logs attribute every action to that user, not a shared service account.

Where is the Datadog api key stored?

Can I limit what the agent is allowed to do in Datadog?

What happens when a user revokes Datadog access?

Can the agent query metrics from other Datadog organizations in a multi-org setup?

Start in your coding agent

Up and running in one command

Install the Scalekit skill in your editor of choice. Connector, auth, tools, prompt, all wired up

Claude Code REPL

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/plugin marketplace add scalekit-inc/claude-code-authstack
/plugin install agentkit@scalekit-auth-stack

Cursor Code REPL

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# ~/.cursor/mcp.json
{
""mcpServers"": {
""datadog"": {
""url"": ""https://mcp.scalekit.com/datadog"",
""headers"": { ""Authorization"": ""Bearer $SCALEKIT_TOKEN"" }
}
}
}

Codex Code REPL

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# ~/.codex/config.toml
[mcp_servers.datadog]
url = ""https://mcp.scalekit.com/datadog""
auth_env = ""SCALEKIT_TOKEN""

Copilot Code REPL

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# .vscode/mcp.json
{
""servers"": {
""datadog"": {
""url"": ""https://mcp.scalekit.com/datadog"",
""type"": ""http""
}
}
}