I Built an AI Agent That Checks Before It Answers

Developer Akanksha Sharma has introduced ContextGuide, an AI agent designed to improve the accuracy of technical responses by prioritizing external verification. Recognizing that LLMs often hallucinate or lack specific context, the project integrates Sanity Context and the Model Context Protocol (MCP) to create a structured knowledge retrieval system. Instead of relying solely on internal training data, the agent queries a curated knowledge base before generating an answer. This approach allows the AI to provide sources, identify conflicting information within documentation, and admit when it needs to verify facts. By shifting the workflow from a direct 'Question to Answer' model to a 'Question to Context to Answer' process, ContextGuide aims to move away from the expectation that AI should know everything, focusing instead on building systems that know when and where to look for reliable information.