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Tutorial: Build a Consent-Gated AI Knowledge Pipeline for Community Chat

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A new developer tutorial warns against building MCP servers that treat community chat history as an automatic knowledge source for AI assistants, arguing that authors never explicitly consented to such reuse. The guide proposes a safer architecture where messages become AI-accessible only after passing through explicit author consent and human moderator review. The pipeline, built using TypeScript and Tencent RTC's Social Messaging platform, tracks each message through defined lifecycle states including awaiting consent, under review, published, suspended, and revoked. Any edit to a source message automatically suspends the published knowledge record until the new version completes the full consent-and-review cycle again. The core design principle is that the MCP search layer can only access deliberately approved records, keeping consent, scope, and publication decisions in the hands of humans rather than AI models.

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