Mock Data Orchestrator
Orchestrates AI-generated mock data for integration tests through the Model Context Protocol.
About
Traditional mock data creation for web application testing is a tedious, time-consuming process involving manual fixtures and high maintenance. Mock Data Orchestrator introduces a paradigm shift by enabling AI-generated, interactive, and evolvable mock data. It achieves this by pairing a WebSocket batch bridge with Model Context Protocol (MCP) tooling, seamlessly moving intercepted requests from tests to AI helpers like Cursor or Claude Desktop, and efficiently delivering fulfilled mock data back to the test runner.
Key Features
- Exposes MCP tools (`get_pending_batches`, `provide_batch_mock_data`) for AI agent interaction
- Orchestrates AI-generated mock data via the Model Context Protocol (MCP)
- Allows detailed request descriptions using metadata (OpenAPI/JSON Schema, instructions) for AI guidance
- 1 GitHub stars
- Provides a WebSocket batch bridge for real-time interception and fulfillment of requests
- Automatically batches concurrent network interceptions for efficient processing
Use Cases
- Automating mock data generation for integration tests to reduce manual effort
- Providing realistic and dynamic mock data for complex and evolving test scenarios
- Integrating AI agents (e.g., Cursor, Claude Desktop) directly into testing workflows for data provision
Sponsored