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Faker
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6 months ago
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2 months ago
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Documentation & install
Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.
Installation
Add the following to your MCP client configuration file.
Configuration
View docs{
"mcpServers": {
"funsjanssen-faker-mcp": {
"command": "npx",
"args": [
"faker-mcp-server"
]
}
}
}You can generate realistic, test-friendly data on demand with Faker MCP Server. It plugs into MCP-compatible clients to create fake person, company, and custom datasets quickly, with repeatable results when you seed generation and support for multiple locales for realistic testing across regions.
How to use
You use the server by connecting via an MCP client and selecting one of the provided data generation tools. Each request specifies the tool name and the desired parameters, such as how many records to generate, locale, and whether to include optional fields. Start with a simple run to see the structure of the data, then add relationships, seeding, and locale variations to fit your testing needs.
How to install
Prerequisites: you need Node.js 18 or newer and an MCP-compatible client.
// Step 1: ensure Node.js is installed
node --version
// Step 2: ensure an MCP client is available (example: Claude Desktop, Cline, Cursor)
// You will integrate the Faker MCP Server through your MCP client configuration
{
## Add Faker MCP Server to your MCP client configuration
{ "mcpServers": { "faker": { "command": "npx", "args": ["faker-mcp-server"] } } }
Note: This snippet shows the runtime command and arguments you use in your client configuration to start the local MCP server process.
Start and test locally
After you configure the client, start the MCP server through the client’s interface. Once running, you can invoke the available tools to generate data and inspect responses in real time.
Available tools summary
The Faker MCP Server provides four main tools for data generation. You can combine these in sequences to build larger, realistic datasets for seeding, API testing, and UI demos.
Available tools
generate-person
Generates realistic person data including names, emails, phone numbers, and addresses with options for locale, seed, and included fields.
generate-company
Generates company data including names, industries, contact information, and addresses with optional website and founding year.
generate-dataset
Creates structured datasets with multiple entities and optional referential relationships between them for complex testing.
generate-custom
Generates data following custom patterns such as regex, enums, formats, and numeric ranges.