- USER DATA
- B2B DATA
- CATALOG DATA
- HUMAN REVIEW
Short answer
How can I use AI to seed my dev database?
You tell your AI what kind of data you need, and it uses Faker to pull specific records for users, companies, or products. This gives you a structured set of data ready for your local environment.
Data generation outcomes
Where your data lands.
The AI handles the heavy lifting of record creation.
USER DATA
Populate user profiles
The AI pulls realistic user identities. You get a list of names, emails, and profiles to test authentication or user settings.
B2B DATA
Build company lists
Generate entire organizations. This provides the company names and details needed to test multi-tenant or B2B logic.
CATALOG DATA
Create product sets
The AI builds product catalogs. You'll have a full set of items to test e-commerce or inventory workflows.
HUMAN REVIEW
Verify custom schemas
If you need something highly specific, the AI builds it based on your rules. You then check the output to ensure it fits your exact requirements.
The workflow
What your AI does when the request arrives.
Your AI acts as the bridge between your intent and the structured data tools.
Define the schema
You describe the specific fields or types of entities you need for your test run.
get_customFetch user records
The AI pulls a batch of realistic user identities based on your description.
get_usersFetch company records
The AI generates a list of organizations to populate your business-level tables.
get_companiesFetch product records
The AI builds out product catalogs to fill your inventory or storefront tables.
get_products
Try it
Copy these to start.
Use these prompts to trigger data generation immediately.
Starting points
Replace the bracketed text with your specific needs, like the number of users or specific industry names.
Faker API Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_1d6UeDZa3GxcUtj29pBEYYPnwezDodnKDwlrsATh/mcpClaude Desktop
Follow the steps below to connect in seconds.
- 1In Claude Desktop, open Settings → Connectors.
- 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
- 3Click Add and start a new chat — Faker API capabilities are ready to use.
{
"mcpServers": {
"faker-mcp": {
"url": "https://edge.vinkius.com/vk_preview_1d6UeDZa3GxcUtj29pBEYYPnwezDodnKDwlrsATh/mcp"
}
}
}Generate 50 realistic users with names and email addresses for my local dev environment.
I need a list of 10 tech companies with headquarters in San Francisco to test my B2B dashboard.
Create a set of 20 electronic products with prices and descriptions for my e-commerce test.
Build a custom dataset of 5 users that includes specific job titles and department names.
Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline
Start here
Connect Faker once, then ask.
Just link the MCP to your client. Your credentials stay encrypted, and you can start generating data right away.
Connect Faker to your AIFAQ
How this task behaves.
- 01
Can the AI write these records directly into my SQL database?
No. The AI generates the data through the MCP, and you then copy that data into your database.
- 02
Can I ask for specific data formats like JSON or CSV?
Yes. You can tell your AI how to format the output so it's ready for your import scripts.
- 03
Will the AI delete any of my existing local data?
No. This MCP only has tools to get and generate data. It cannot modify or delete your local files or databases.
- 04
Can I generate data for fields not listed in the tools?
Yes. You can use the custom tool to define specific, non-standard fields you need for your testing.
- 05
Does the AI decide the data values on its own?
The AI uses your instructions to guide the generation, but it uses the Faker tools to ensure the values are realistic.
More questions about Faker? The Connector page answers them. See everything the Faker Connector can do
Connect Faker API to Claude, Cursor, ChatGPT & more
