Answering from a living doc
The team's processes live in a Coda doc. Someone asks how expense approvals work; Memtro finds the doc, exports the right page as Markdown and answers with the current text.
Read your Coda docs, pages and tables without opening them.
Connect Coda with an API token and Memtro can find docs by title, read any page as Markdown, describe tables and views, and pull rows filtered by a column value. Today it only reads; actions arrive marked and granted by name.
Ask in plain English from chat, your editor, a scheduled job or your own agent. The model picks the right Coda tool, reads what it needs, and answers with the source cited.
The team's processes live in a Coda doc. Someone asks how expense approvals work; Memtro finds the doc, exports the right page as Markdown and answers with the current text.
A customer success lead asks who owns the Northwind renewal. Memtro lists the Accounts table's columns, queries rows where Account equals Northwind and reads back the owner and renewal date.
Questions people ask once Coda 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 Coda in Memtro, with the rest of their stack attached.
A record in Coda 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 Coda 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.