Developer Builds AI Agent That Queries a Knowledge Base Before Answering

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A developer created ContextGuide, an AI agent designed to consult a structured knowledge base before generating responses to user questions. The tool uses Sanity for content organization, Sanity Context for querying, and the Model Context Protocol (MCP) to connect the agent to retrieved information. Unlike standard AI models that answer directly from training data, ContextGuide follows a Question–Context–Answer pipeline to ground its responses in relevant documentation. The agent can also flag contradictions between sources rather than defaulting to a single confident answer. The project was built to address the common problem of AI responses that sound accurate but lack sufficient contextual grounding.

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