Failed payment follow-up
A payment bounces for insufficient funds; Memtro records who it was for, how much and whether GoCardless will retry, so support has the context when the customer calls.
Every Direct Debit, mandate and payout at hand.
Memtro reads your GoCardless account so the model can tell you which payments failed and why, which customers have active mandates, what subscriptions are running and when payouts land. Failures, chargebacks, cancelled mandates and payouts are remembered as they happen.
Ask in plain English from chat, your editor, a scheduled job or your own agent. The model picks the right GoCardless tool, reads what it needs, and answers with the source cited.
A payment bounces for insufficient funds; Memtro records who it was for, how much and whether GoCardless will retry, so support has the context when the customer calls.
Ask what last Friday's payout covered and Memtro breaks it into the payments, refunds and fees it contained.
Questions people ask once GoCardless is connected. In agent mode each one also checks the other systems that know about the same people, companies or identifiers.
Teams that get the most from GoCardless in Memtro, with the rest of their stack attached.
A record in GoCardless is rarely the whole story. Connect the systems that hold the rest and the agent cross-references them by default, then remembers what it learned so the next question starts further along.
Using something else for the same job, or both? Each connector has its own tools; connect as many as you like.
Chat in the dashboard, the OpenAI-compatible API, scheduled jobs, and any MCP client: Claude Code, OpenCode, Cursor, Claude Desktop. The GoCardless tools are the same everywhere.
Set it up as an MCP server →Clients and agents →Seven-day free trial, then one monthly price per organisation. Connectors, jobs and memory are never metered.