How connector data sources power Leash automations
Leash connectors let automations use external accounts as data sources and report destinations while staying attached to the same agent identity.
Why it matters
An automation is only useful if it can read the right data and report in the right place. Connectors provide that context without breaking the identity model.
Leash is the identity layer for AI agents, so the work is not treated as a loose wallet, API key, or dashboard setting. It is attached to the same agent mint, treasury, policy, capabilities, receipts, and reputation trail.
How Leash handles it
Leash treats connected services as capabilities attached to the active agent. Automations can reference those connections and record delivery status separately from run success.
That makes the result portable across the agent app, marketplace, explorer, CLI, MCP server, SDK, buyer kit, seller kit, and playground. The surface can change, but the identity and proof trail stay the same.
Implementation checklist
Connect the account, choose whether it is a source or destination, describe the automation in natural language, and verify the report policy before enabling it.
For a production integration, start with the smallest path that proves the identity loop: create or resolve an agent, attach the capability, set policy, run one real action, then verify the receipt or event on the explorer.
Prompt a connector-backed automation
Use my Gmail connection as a source.
Every weekday morning, summarize billing-related messages.
Report only the summary in Telegram and keep full history in Leash.FAQ
Does every automation need report delivery?
No. Some automations only need history. Others should report to chat, webhook, or another connected destination.
What happens when delivery fails?
The run should still land in history, with delivery status recording the failure for debugging.