Integrating Amazon Bedrock Knowledge Bases into Your Assistants: Here's How Its MCP Server Works

What is the Amazon Bedrock Knowledge Bases Retrieval MCP Server?
This MCP server connects LLM-based assistants with the Knowledge Bases (KBs) you've set up within Amazon Bedrock. Thanks to this integration, the model can retrieve relevant passages from embedded knowledge bases and your own business data.
It’s a direct and secure way to make a model understand exactly what you know, without needing to retrain it or expose sensitive data.

What exactly does this server do?
The MCP Server acts as a bridge between your Knowledge Base in Bedrock and the LLM you are using, enabling semantic search functionality over your corporate data.
The core function that this server exposes to the model is retrieve, and it works with the following capabilities:
Accepts questions or search phrases.
Queries the associated KBs.
Returns relevant documents or snippets as context for the model.
The entire process is transparent and structured according to the MCP protocol.

What type of data can it retrieve?
The Knowledge Bases in Bedrock can include business documents, manuals, internal articles, policies, emails, historical tickets, or any other type of textual data. This server allows LLMs to:
Access this data without exposing the source directly.
Answer complex questions using internal material.
Reference specific knowledge fragments.
All of this happens in real-time, with auditing, and without needing to retrain the model.

Why is it important?
This server represents a strong use case for RAG (retrieval-augmented generation) within corporate environments. Some key benefits include:
Directly connects to your own data.
Requires zero fine-tuning.
Works with Amazon Bedrock models while respecting your security policies.
Allows LLMs to respond as if they truly know your organization.
Real-world use cases
A legal assistant that accesses internal policies and contracts.
A sales co-pilot that can query pricing procedures and past proposals.
A support bot that answers based on your internal solution base.
A financial analyst who consults historical reports directly from a structured KB.
Typical workflow
You create a Knowledge Base in Amazon Bedrock, connected to S3 or a structured repository.
You configure this MCP Server to expose the KB as a retrieve tool.
The model uses MCP to query the KB for each relevant question.
The model generates responses using the most relevant passages from your information.
Technical considerations
You need permissions to access Bedrock and its KB API.
You can define multiple KBs and filter them by type, domain, or confidentiality.
Everything is controlled through YAML configuration or directly via code if you extend the server.

Conclusion
The Amazon Bedrock Knowledge Bases MCP Server takes the concept of the corporate co-pilot to a new level: one where AI truly understands your organization, your terminology, your documents, and your history.
Instead of relying on generalist models, this server lets you have an assistant tailored to your business, built on your data, and aligned with your security and privacy policies.