AWS Knowledge Base MCP
Official Amazon Bedrock Knowledge Base MCP server — connect AI to your AWS knowledge bases for RAG-powered enterprise search.
// Try it now
"Search my AWS Bedrock Knowledge Base for documentation about our authentication setup"
- ! Bedrock Knowledge Bases cost money per query and per data store — monitor usage
- ! IAM permissions need Bedrock read access — misconfigured roles fail silently
- ! Indexing is not instant — newly uploaded docs may take minutes to become queryable
API key or simple config
// When to use
- You've set up AWS Bedrock Knowledge Bases with your company docs
- You need RAG (retrieval-augmented generation) over private enterprise content
- You're building on AWS and want to use Bedrock's managed vector storage
- You need compliance-friendly AI retrieval within your AWS account
// When NOT to use
- You don't use AWS or Bedrock (use a different RAG provider)
- You need public web search — this is for private KB only
- You haven't indexed your documents into Bedrock yet (that's the prerequisite)
// Usage Scenarios
Internal Doc Retrieval
Answer questions by retrieving from your private Bedrock-indexed documents.
Example prompt
"Search our internal onboarding knowledge base for the process to request new AWS IAM roles"
Compliance-Friendly Q&A
Keep retrieval within your AWS account for regulated data.
Example prompt
"Look up the incident response policy from our compliance KB and summarize the steps"
Multi-KB Routing
Query different knowledge bases depending on the question.
Example prompt
"Search the engineering KB for the deploy rollback procedure"
// About
Plain English
Imagine your company has years of policies, runbooks, onboarding guides, and product docs locked away in PDFs and wikis on AWS. Finding the right answer means search-and-scroll until something matches. This server gives your AI assistant a direct line to that material. It connects to Amazon Bedrock Knowledge Bases — AWS's managed search system for your private documents. You ask Claude a plain English question like 'What's our policy for issuing new IAM credentials?' and Claude looks inside your indexed documents, pulls the relevant passages, and writes an answer grounded in what your company actually wrote. The value: nothing leaves your AWS account, retrieval stays under your existing security controls, and you stop hunting through Confluence pages. The catch: someone has to load and index the documents into Bedrock first, and AWS bills per query and per stored vector. Best for teams already running on AWS who want a private 'ask the company' assistant without standing up a separate vector database.
The official AWS Knowledge Base MCP server connects AI assistants to Amazon Bedrock Knowledge Bases. Perform retrieval-augmented generation (RAG) over your enterprise documents, PDFs, and data sources stored in AWS.
Maintained by AWS with enterprise-grade security and scalability. Ideal for organizations that store documentation and knowledge in AWS.
// Use Cases
- Search enterprise documentation through AI
- Build RAG applications over AWS-hosted documents
- Query internal knowledge bases conversationally
- Integrate company docs with AI assistants
// Works With
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