Build an AI-Powered API Testing Agent
Create an intelligent agent that automatically generates, executes, and validates API test cases using LLM reasoning and code execution capabilities.
Agent Framework
Core agent orchestration for planning test strategies, generating test cases, and reasoning about API behavior
Graph-based agent architecture lets you model the test lifecycle as nodes (plan → generate → execute → validate → report), with conditional edges for retry and error-handling flows
Role-based multi-agent setup where specialized agents handle test generation, execution, and validation as distinct crew members
Pydantic-native structured outputs ensure generated test cases and assertions conform to strict schemas, reducing hallucinated test logic
Code Execution & Sandboxing
Secure runtime environment for executing generated API test scripts without risking the host system
LLM Gateway & Routing
Unified access to language models for test generation, with fallback routing and cost control
Proxy 100+ LLM providers through one API — use fast models for simple assertion generation and powerful models for complex edge-case reasoning, with automatic fallback
Blazing fast AI gateway with built-in guardrails to prevent the agent from generating harmful or nonsensical test payloads
Observability & Evaluation
Track agent decisions, measure test quality, and evaluate whether generated tests actually catch real bugs
Trace every agent step from test planning through execution — see which LLM calls generated good tests vs. false positives, with cost tracking per test run
Evaluate and red-team the agent's test generation prompts to ensure consistent quality across different API schemas and edge cases