How Sanity Context & MCP Supercharged AI Customer Support in Basegent & Bucket Space

Описание и применение

Интеграция Sanity Context MCP в платформу Basegent позволяет AI‑ассистенту выдавать точные ответы, учитывая актуальные политики и условия, и устраняет проблемы традиционного RAG.

Задача

Traditional vector search treats company documentation like a bag of text chunks, leading to outdated policy quoting, lack of conditional logic for multi‑dimensional entitlements, and hallucinations on generic product names.

Результат

By modeling policies as structured documents in Sanity and querying them live via MCP, Basegent delivers accurate, context‑aware support, eliminates policy conflicts, and reduces hallucinations.

Рабочий процесс

• Integrate Sanity into Basegent via SanityContextSourceAdapter and BYOK inference engine
• Set up Sanity Knowledge Base & Context MCP with structured supportPolicy documents and conflict detection
• Deploy Basegent chat widget in Bucket Space, passing authenticated user tokens to query Sanity live

Доказательства

Traditional vector search treats company documentation like a bag of text chunks.

Источник

Support policies shouldn’t be plain blobs of text. In Sanity Studio, we modeled supportPolicy documents with explicit schema constraints.

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Built a first‑party SanityContextSourceAdapter directly into Basegent that talks to Sanity’s hosted MCP endpoint, paired with a multi‑provider Bring‑Your‑Own‑Key inference engine.

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