Agent Framework RAG for Agents: Giving Your Agent the Right Context

Short summary

Implement RAG in Microsoft Agent Framework by exposing retrieval as a controlled tool rather than embedding all knowledge in prompts. Agents call SearchKnowledgeAsync to fetch relevant company documents from vector stores or search indexes, receiving only focused results. The post covers chunking strategies, metadata filtering, security boundaries, and includes C# code examples.

• •Expose retrieval as a focused tool that agents call when needed, not by stuffing documents into prompts
• •Use vector stores (Azure AI Search, pgvector, Qdrant) with metadata filters for security and relevance
• •Agents rewrite user queries and control retrieval parameters to fetch appropriately scoped context

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