Guides
Table & Database
Browse every guide in this topic.
- Connect AI Agents to Fusebase Dashboards with MCP
- Sub-tables – Quick Guide
- Exporting a Table to CSV – Quick Guide
- Importing into a table from CSV – Quick Guide
- Duplicating database and table
- Users column – Quick guide
- Kanban view in Fusebase – Quick Guide
- Database automation – A guide to creating workflows
- Relation Records & Lookup – Quick Guide
- Embed Fusebase databases and dashboards into portals
- Custom Databases – Quick Guide
- Column groups – simplifying data display in detailed view
- Filtering and Sorting – Quick Guide
- Custom views – building a dashboard for ourselves
- Custom columns in the dashboard/table – building your own CRM in Fusebase
Frequently asked questions
What is the difference between a table and a database?
A table on a page holds structured rows for the people reading that page. A database is a separate store you can filter, view as a kanban board and reuse in more than one place. If the same records need to appear on several pages or drive an automation, build a database rather than a page table.
Can I link records between tables?
Relation fields connect a record in one table to records in another, and lookup fields pull a value across that link so nobody retypes it. Sub-tables let a single record carry its own set of rows, which fits cases such as a project with its tasks or an account with its invoices.
How do I get existing data in and out?
You can import into a table from a CSV file and export a table back to CSV, so a spreadsheet you already maintain can become a working database and a copy can go to whoever needs one. Duplicating a database or table is the quick route when a new project needs the same structure.
Can a client see one database without seeing everything else?
Yes. A database or dashboard can be embedded into a portal, so a client sees the records meant for them in their own space while the rest stays on your side. What each person can view or change follows the access you set, not the fact that the data lives in one system.
Can an AI agent work with our data directly?
Agents can connect to FuseBase dashboards through MCP, a standard way of giving an AI tool access to a system, and can read and update records inside the permissions you grant. Give an agent the narrowest access that lets it do its job, and check what it writes before relying on it.
How is this different from pasting work into a chatbot?
A general chat tool has no standing role, no access to your client records and no rules about what it may act on. An AI coworker in FuseBase is set up against real work, with scoped permissions, inside the process it is helping with.
Who decides what an agent is allowed to touch?
You do, through the same permission system that governs people. An agent operates inside scoped access rather than above it, which is what makes delegating any of the client facing work reasonable in the first place.
Can each client get their own space?
Yes. Each client can have a portal of its own, branded to you, holding only the documents, updates and approvals that client should see. Access is set per person and per item rather than per workspace.
How do we prepare for tools that do not exist yet?
By putting the work somewhere it can be built on: structured records, clear permissions and a client facing surface that is already connected. Tools change quickly, but work that lives in a connected process is what a future tool can pick up.