MCP server testing is the practice of validating that a Model Context Protocol server exposes the right tools, passes the right context, preserves session state across turns, and returns outputs an LLM can use correctly in real agentic workflows. For QA teams building AI products, this means testing not just API responses but complete tool-driven… Continue reading How to Test MCP Servers with DeepEval
Tag: LLM-as-a-Judge
Agentic Testing and QA: An AI Framework for Chatbots & RAG
At a Glance Why Traditional Automation Fails AI Systems — and What to Do Instead Pass/fail is not enough when your system can hallucinate, drift, or refuse incorrectly. The core shift: AI systems require evaluation across multiple quality dimensions — relevance, faithfulness, hallucination risk, toxicity, and retrieval grounding — not a single pass/fail assertion. Golden… Continue reading Agentic Testing and QA: An AI Framework for Chatbots & RAG