Bring Rag
to Mastra AI

Connect your Amazon Bedrock account to any AI agent and empower it with managed vector databases, enterprise RAG workflows, and semantic search directly inside AWS.

What you can do

• Managed RAG — Generate grounded LLM responses using internal document sets in a single explicit call
• Semantic Retrieval — Query vector indexes to retrieve exact top-K text chunks and their origin document URLs
• Data Sources — Inspect and paginate attached storage buckets feeding the knowledge base
• Ingestion Jobs — Track real-time syncing status of chunking pipelines mapping documents across the vector layout
• Knowledge Base Introspection — List available vector stores and exact embedding models assigned directly to your region

How it works

1. Subscribe to this server
2. Enter your AWS IAM Role/User Access Credentials
3. Start augmenting your agent's context from Claude, Cursor, or any MCP-compatible client

Eliminate the need to build custom vector pipelines. Your agent queries massive corporate datasets precisely where they reside in AWS.

Who is this for?

• AI Developers — build RAG workflows rapidly without hosting databases or maintaining chunking sync logic
• Cloud Architects — audit ingestion status and check origin document mappings securely from your chat interface
• Data Scientists — prototype context-grounded queries instantly and trace accuracy against exact data chunks