Api Response Mocker

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by dkyazzentwatwa Β· vlatest Β· Repository

Provides API guidance and assistance for agent workflows.

Install on your platform

We auto-selected Claude Code based on this skill’s supported platforms.

1

Run in terminal (recommended)

terminal
claude mcp add api-response-mocker npx -- -y @trustedskills/api-response-mocker
2

Or manually add to ~/.claude/settings.json

~/.claude/settings.json
{
  "mcpServers": {
    "api-response-mocker": {
      "command": "npx",
      "args": [
        "-y",
        "@trustedskills/api-response-mocker"
      ]
    }
  }
}

Requires Claude Code (claude CLI). Run claude --version to verify your install.

About This Skill

What it does

The Api Response Mocker skill allows AI agents to generate realistic mock API responses with fake data using the Faker library. It enables defining response structures (schemas) and populating them with synthetic, believable data in various formats like JSON and XML. The tool supports complex nested objects, arrays of objects, and even referencing other mock data for creating relationships between different entities.

When to use it

  • Development & Testing: Generate sample API responses when building or testing applications that consume APIs.
  • Documentation: Create example API responses for documentation purposes.
  • Prototyping: Quickly create realistic data for prototyping user interfaces or workflows.
  • Demonstrations: Generate mock data to showcase API functionality without relying on live backend systems.

Key capabilities

  • Schema-Based Generation: Define the structure of the API response using a schema.
  • Faker Integration: Uses Faker to generate realistic fake data for various fields.
  • Nested Objects & Arrays: Supports complex, hierarchical data structures.
  • Relationships: Allows referencing other mock data within responses.
  • Multiple Formats: Generates output in JSON and XML formats.
  • Reproducibility: Uses a seed value to generate the same mock data consistently.

Example prompts

  • "Generate a JSON response for a user object with fields id, name, email, and created_at."
  • "Create 10 mock product objects in JSON format using the schema defined in 'product.json'."
  • "Show me a preview of a customer API response based on the 'customer.json' schema without saving it to a file."

Tips & gotchas

  • You need Python installed to use this skill, as it’s implemented as a Python script.
  • The schemas define the structure and data types using Faker provider names (e.g., "uuid", "name"). Refer to the available data type documentation for valid providers.
  • Using a seed value ensures that you generate the same mock data each time, which is useful for testing and reproducibility.

Tags

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Details

Version
vlatest
License
Author
dkyazzentwatwa
Installs
32

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Passed automated security scans.