Hey HN - Mert here, maker of MoneyCo (thecompany.money). MoneyCo connects to multiple Quickbooks and Xero accounts by default and lets you do your bookkeeping using a coding agent.

I got here after talking to multiple accountants and hearing them struggle to use Claude, Codex, Hermes and OpenClaw. The difficulties they had were classic:

1. QBO and Xero MCPs are brittle and allow limited access 2. They were only able to figure out how to run these locally 3. LLMs not being good at math 4. Configuring client memory

Coding agents disguised as one that does accounting felt like a simple yet powerful idea as a solution:

1. We connect to QBO and Xero using API instead of MCP and make it easy for multiple accounts connection 2. We deploy all client files along with `pi --rpc` in a sandbox so all can work on the cloud 3. A coding agent can simply write code for deterministic computations and run tests to catch inaccuracies 4. Each chat made progressively gets stored in the persistent sandbox meaning that agent can search through older conversations to look into its memory

I had to rebuild some of the architecture here several times as it required building a durable, persistent cloud coding agent essentially. Each client is configured almost as a repo/filesystem of its own that lives there forever, including the agent chats made by the users.

Stack is

- django for backend - modal for sandboxes - streaming uses two paths (1) for livestreaming (2) for durable background ones. Both use Cloudflare durable objects - frontend in vite - agent is a fork of pi - no MCP usage at all. For OCR, memory search, IRS docs search and further things, there is an embedded cli called `tlmc` that agent is encouraged to use in its system prompt

HN is not the right place to launch an accounting product however I thought the way this is built might be relevant to cloud agents and how to architect them.

Please let me know any feedback, requests and most of all any brutal feedback!