WORLDTECHFine-grained access control for Amazon Bedrock Managed Knowledge Base tools
What happened
In a traditional application, the application code determines who the signed-in user is and searches with that user’s permissions. Learn how to expose an Amazon Bedrock Managed Knowledge Base to AI agents (AI that carries out multi-step tasks rather than answering one question) as MCP tools through Amazon Bedrock AgentCore Gateway while keeping per-user access control.
A request interceptor injects verified identity, Policy in AgentCore validates it independently, and a resource-based policy restricts direct access to the knowledge base. More enterprises are building AI agents into their daily work, and a common pattern is an agent that searches internal documents to compose its answers.
A single organization might soon run hundreds of agents, each connected to many data sources and tools. Consider AnyCompany, a fictional company that builds an internal assistant shared by all employees.
The agent writes its own search queries and keeps searching internal documents until it has enough information. Artificial Intelligence More enterprises are building AI agents into their daily work, and a common pattern is an agent that searches internal documents to compose its answers.
Employees in department B ask the same assistant the same question. If the application doesn’t scope searches to each user, the department B business plan can end up in an answer to an employee in department A.
If you replace the departments with customer companies, the same problem occurs in a multi-tenant software as a service (SaaS (software rented online rather than installed and owned)) architecture where multiple customers share one assistant and knowledge base. Controlling access to multi-tenant data through this agent is harder than in traditional applications.