Datadog ACTION
Search Logs
Search Datadog logs matching a query with support for facets and time ranges. Uses log search syntax:
service:web-app status:error, @http.status_code:>=400, boolean operators (AND, OR, NOT), and wildcards. Set from to now-1h for recent logs. Use Search Metrics to discover metric names or Search Hosts to find host names for filtering. To investigate an incident, use Search Incidents first, then search logs for that time window and service. See the docs- Action
- Read only
- API key
- SDK
- MCP
IMPLEMENTATION
Call this tool
Connect a user's Datadog account once, then configure and run Search Logs from your backend or agent.
import { PipedreamClient } from "@pipedream/sdk"
const pd = new PipedreamClient({
projectId: process.env.PIPEDREAM_PROJECT_ID!,
clientId: process.env.PIPEDREAM_CLIENT_ID!,
clientSecret: process.env.PIPEDREAM_CLIENT_SECRET!,
projectEnvironment: "production",
})
const result = await pd.actions.run({
id: "datadog-search-logs",
externalUserId: "{external_user_id}", // any stable ID for this user in your system
configuredProps: {
datadog: { authProvisionId: "apn_xxxxxxx" },
region: "Region",
query: "Query",
},
})
console.log(result)curl -X POST https://api.pipedream.com/v1/connect/{project_id}/actions/run \
-H "Content-Type: application/json" \
-H "X-PD-Environment: production" \
-H "Authorization: Bearer {access_token}" \
-d '{
"external_user_id": "{external_user_id}",
"id": "datadog-search-logs",
"configured_props": {
"datadog": { "authProvisionId": "apn_xxxxxxx" },
"region": "Region",
"query": "Query"
}
}'// accessToken: mint a short-lived token with the Connect SDK — see the MCP guide
const transport = new StreamableHTTPClientTransport(
new URL("https://remote.mcp.pipedream.net/v3"),
{
requestInit: {
headers: {
Authorization: `Bearer ${accessToken}`,
"x-pd-project-id": "{project_id}",
"x-pd-environment": "production",
"x-pd-external-user-id": "{external_user_id}", // any stable ID for this user in your system
"x-pd-app-slug": "datadog",
},
},
},
)
const mcp = new Client({ name: "my-agent", version: "1.0.0" })
await mcp.connect(transport)
const { tools } = await mcp.listTools()
// listTools() hands your model this tool's input schema, so it can
// fill the arguments itself:
const result = await mcp.callTool({
name: "datadog-search-logs",
arguments: {
region: "Region",
query: "Query",
},
})SCHEMA
Inputs
Pipedream supplies the connected account. Your application provides the operation-specific values below. Dynamic inputs are resolved against that user's account.
| Property | Type | Description |
|---|---|---|
region Region | string | The regional site for a Datadog customer Required |
query Query | string | Search query following log search syntax. E.g. service:web-app status:error Required |
from From | string | Minimum timestamp for requested logs. Supports date math (e.g. now-15m, now-24h), ISO-8601, or epoch ms. Defaults to 15 minutes ago. Optional |
to To | string | Maximum timestamp for requested logs. Supports date math (e.g. now), ISO-8601, or epoch ms. Defaults to now. Optional |
indexes Indexes | string[] | List of log index names to search. Defaults to all indexes. Optional |
limit Max Results | integer | Maximum number of logs to return per page. Default 10, max 1000. Optional |
sort Sort | string | Sort order for results. Optional |
REFERENCE
Tool details
Behavior hints are published with the component in the Pipedream registry and surface as MCP tool annotations, so an agent can reason about a tool before it calls it.
- Registry key
- datadog-search-logs
- Version
- 1.0.2
- App
- Datadog
- Authentication
- API key
- Read-only
- Yes
- Destructive
- No
- Open world
- Yes
- Source
- View on GitHub ↗