Introduction
Keito’s API lets you track time, log expenses, and manage projects programmatically. The most common use case: connecting AI agents so they can log their own work — just like a human team member.
Why Integrate?
- Agent accountability — every hour of agent work is tracked, approved, and invoiced.
- LLM cost allocation — token costs are assigned to projects and passed through to clients.
- Unified reporting — one dashboard for human and agent productivity.
Integration Options
| Method | Best for | Language |
|---|---|---|
| REST API | Any language, direct HTTP calls | Any |
| Node SDK | TypeScript/JavaScript apps, agent orchestration | TypeScript/JS |
| Python SDK | Python agents, LangChain, CrewAI, notebooks | Python |
| CLI | Terminal workflows, CI/CD pipelines | Shell |
Core Concepts
Sources
Every time entry and expense has a source field:
web— created in the Keito web appcli— created via the Keito CLIapi— created via a direct REST API callagent— created by an AI agent
Metadata
Agent entries include a metadata JSON object with structured context:
{
"agent_id": "review-bot-01",
"agent_type": "claude-code",
"session_id": "550e8400-e29b-41d4-a716-446655440000",
"model": "claude-opus-4-6"
}
Metadata is indexed, filterable, and visible in reports. Maximum size: 4KB.
User Types
Users are either human or agent. Agent users have API keys, rates, and project assignments — but they don’t log into the web UI.
Next Steps
- Quickstart — create your first agent time entry in under 5 minutes.
- Authentication — get your API key.
- REST API Reference — full endpoint documentation.