Data Faker (DATA_FAKER)

Creates realistic but invented test data, for example names, addresses or companies, as a list. Useful to try out a pipeline without real data.

Category: Data Sources · Deployed: yes · Tool-capable: yes

Ports

Port Kind Purpose

Result (out_result)

Output

The list of generated entries

Tool (tool_mcp)

Tool

Wire to an Agent’s Tools port

No input port — it creates data and needs nothing.

Properties

Field Required Meaning

Provider (provider)

Yes

The kind of data: Address, Animal, Color, Company, Finance, Internet, Job, Lorem, Nation, Person, PhoneNumber or Vehicle

Fields (fields)

Yes

Which values each entry gets, for example firstName and lastName for Person. The list depends on the Provider

Row Count (rowCount)

Marked as required

How many entries to create. Empty means 10. More entries give the next module a longer list, which can make an agent slower and more costly

Choose the Provider first. Changing the Provider clears the Fields.

What happens at run time

  • The result is a JSON list. Each entry has the chosen fields, for example [{"firstName": "Anna", "lastName": "Berg"}, …].

  • Every run creates new random values.

  • As a tool: the agent calls it without any values and gets the configured list. The agent sees a short generated description, for example "Generates 10 row(s) of synthetic Person test data."

  • As a step: it has no input, so nothing can be wired to it. A chat run starts at Chat Input and a scheduled run at the Scheduler, and each runs only modules wired to its start. So as a step, Data Faker runs only in a chat of a pipeline without a Chat Input, and never in a scheduled run. See Chat Input.

When the pipeline is checked

Provider and Fields must be filled. If one is empty, the app lists it and refuses to assign the pipeline to an agent.

Use cases

  • Build a pipeline before real data exists: let an agent use it as a tool in place of a database or API.

  • Test the size limits: create a long list and see how the next modules cope.

  • Demos without real customer data.

Notes

  • This is a test aid. Replace it with the real source before you go live. Nothing warns you when a live pipeline still uses invented data.