Clockify ACTION
Log Time Entry
Logs a completed time entry with an explicit start and end time in Clockify — use this to backfill time already tracked elsewhere. Use Start Timer instead if you want to start a running timer with no end time yet. See the documentation, or logging for another member when
User is set- Action
- Writes data
- API key
- SDK
- MCP
IMPLEMENTATION
Call this tool
Connect a user's Clockify account once, then configure and run Log Time Entry 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: "clockify-log-time-entry",
externalUserId: "{external_user_id}", // any stable ID for this user in your system
configuredProps: {
clockify: { authProvisionId: "apn_xxxxxxx" },
workspaceId: "Workspace",
projectId: "Project",
},
})
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": "clockify-log-time-entry",
"configured_props": {
"clockify": { "authProvisionId": "apn_xxxxxxx" },
"workspaceId": "Workspace",
"projectId": "Project"
}
}'// 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": "clockify",
},
},
},
)
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: "clockify-log-time-entry",
arguments: {
workspaceId: "Workspace",
projectId: "Project",
},
})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 |
|---|---|---|
workspaceId Workspace | string | Identifier of a workspace Required Dynamic |
projectId Project | string | Identifier of a project Optional Dynamic |
taskId Task | string | Identifier of a task Optional Dynamic |
userId User | string | Logs the time entry for this workspace member instead of yourself. Leave blank to log it for your own account. Optional Dynamic |
start Start | string | Start date and time of the time entry, in ISO 8601 format. Example: 2026-08-05T09:00:00Z Required |
end End | string | End date and time of the time entry, in ISO 8601 format. Example: 2026-08-05T17:00:00Z Required |
timeEntryDescription Description | string | Description of the time entry Optional |
billable Billable | boolean | Whether the time entry is billable Optional |
tagIds Tags | string[] | Array of tag identifiers Optional Dynamic |
timeEntryType Type | string | The type of the time entry 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
- clockify-log-time-entry
- Version
- 0.0.2
- App
- Clockify
- Authentication
- API key
- Read-only
- No
- Destructive
- No
- Open world
- Yes
- Source
- View on GitHub ↗