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Faker Forge Docs

Complete user guides for Data Generation, API Mocking, and MCP integration, organized for both developers and LLM-driven workflows.

Basics

Getting Started

What Faker Forge does, core concepts, and first successful run.

Getting Started

Faker Forge helps you generate realistic database data, mock APIs with controllable scenarios, and automate both through MCP tools.

What You Can Do

  • Import SQL schemas or migration-like definitions.
  • Generate realistic fake rows with relationship awareness.
  • Edit faker mappings before re-generation.
  • Export generated output as SQL, JSON, CSV, or XML.
  • Build mock APIs with per-endpoint scenarios.
  • Connect AI agents via MCP for generation and mocking workflows.

Product Areas

Data Generation

Use schema parsing plus faker mappings to produce consistent records quickly.

API Mocking

Create mock endpoints with scenarios, status codes, delays, and headers.

MCP

Use authenticated MCP tools so agents can list schemas, generate data, and manage API mocks.

First Successful Run

  1. Go to Generate and upload or paste your schema.
  2. Open a parsed schema page and confirm detected tables.
  3. Set per-table row counts and mapping preferences.
  4. Run generation.
  5. Open Export and download your preferred format.

Key Terms

  • Schema: A parsed database structure used as generation input.
  • Mapping: Faker method selection for each column.
  • Relationship: Parent-child foreign key linkage used during generation.
  • Mock: A named API surface with one or more endpoints.
  • Scenario: A conditional response variant for an endpoint.
  • Codebase Identifier: Stable project key used by MCP to reuse schema or mock context.
  • Use the left menu to move between guides.
  • Use search to jump straight to pages.
  • Use On This Page on the right to jump to sections.
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