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Bedrock KB Retrieval MCP - Amazon Bedrock Knowledge Base Integration

Amazon Bedrock Knowledge Base Retrieval MCP integration with Amazon QuickSuite. This solution creates an MCP integration that enables direct access to Amazon Bedrock Knowledge Bases through QuickSuite using MCP Actions.

Architecture

Bedrock KB Retrieval MCP Architecture

Components:

  • AgentCore Gateway: Amazon Bedrock AgentCore Gateway with Lambda target
  • Lambda Function: Amazon Bedrock Knowledge Base retrieval handler
  • QuickSuite Integration: MCP Actions for conversational AI
  • Amazon Bedrock Knowledge Bases: Document retrieval and semantic search

Purpose

This MCP integration enables:

  • Direct KB Access: Query Amazon Bedrock Knowledge Bases through natural language
  • QuickSuite Integration: Integration using MCP Actions
  • AgentCore Gateway: Gateway with Lambda target and authentication
  • Document Retrieval: Semantic search with reranking and filtering

Project Structure

bedrock-kb-retrieval-mcp/
 app.py                          # CDK deployment entry point
 cdk.json                        # CDK configuration
 pyproject.toml                  # Project dependencies
 tools/                          # Lambda function code
    kb_agentcore_lambda.py     # AgentCore MCP handler
    kb_agentcore_tools.json    # MCP tool definitions
    requirements.txt           # Lambda dependencies
 cdk/                           # Infrastructure code
    bedrock_kb_mcp_stack.py    # AgentCore Gateway stack
    README.md                  # CDK deployment guide
 README.md                      # This file

Quick Start

1. Clone Repository (Sparse Checkout)

# Clone repository with sparse checkout
git clone --filter=blob:none --sparse https://github.com/aws-samples/sample-amazon-quick-suite-knowledge-hub.git
cd sample-amazon-quick-suite-knowledge-hub

# Configure sparse checkout for this integration only
git sparse-checkout set docs/integration/actions/MCP/bedrock-kb-retrieval-mcp
cd docs/integration/actions/MCP/bedrock-kb-retrieval-mcp

2. Deploy AgentCore Gateway

npm install -g aws-cdk
uv sync
cdk deploy --require-approval never

3. Get Outputs

Option 1: AWS Console (Recommended)

  1. Go to AWS CloudFormation in the AWS Console
  2. Find the quicksuite-bedrock-kb-mcp stack
  3. Click on the Outputs tab
  4. Copy the required values for Quick Suite integration

Option 2: CLI Commands 

aws cloudformation describe-stacks --stack-name quicksuite-bedrock-kb-mcp --query 'Stacks[0].Outputs'

Key outputs for QuickSuite Actions:

  • GatewayUrl - AgentCore Gateway endpoint
  • ClientId - OAuth2 client ID
  • ClientSecret - OAuth2 client secret
  • CognitoTokenUrl - OAuth2 token endpoint

Available Tools

Knowledge Base Tools (kb_agentcore_lambda.py)

Tool Purpose Input Output
ListKnowledgeBases Discover available Bedrock Knowledge Bases explanation knowledge_base_mapping, data_sources
QueryKnowledgeBases Natural language retrieval from Knowledge Bases query, knowledge_base_id, options documents, content, scores

ListKnowledgeBases

Purpose: Discover available Bedrock Knowledge Bases and data sources Input: explanation (string): Brief description of why you're listing knowledge bases Output: Knowledge base mapping with IDs, names, descriptions, data sources

QueryKnowledgeBases

Purpose: Natural language retrieval from Bedrock Knowledge Bases Input:

  • query (required): Natural language search query
  • knowledge_base_id (required): Target KB ID
  • number_of_results (optional): Result count (default: 10, max: 100)
  • reranking (optional): Enable reranking (default: false)
  • reranking_model_name (optional): Reranking model ("COHERE" or "AMAZON")
  • data_source_ids (optional): Filter by data sources

Output: Newline-separated JSON documents with content, location, score

QuickSuite Integration

Complete guide to integrate Bedrock KB Retrieval with Amazon QuickSuite using MCP Actions.

Prerequisites

From your CDK deployment, you'll need:

  • GatewayUrl - AgentCore Gateway endpoint
  • ClientId - Cognito Client ID
  • ClientSecret - Cognito Client Secret
  • CognitoTokenUrl - OAuth2 token endpoint

Configure MCP Action in QuickSuite

Step 1: Access Integrations

  1. Navigate to Integrations in Amazon QuickSuite
  2. Click on Actions
  3. Click the + button for Model Context Protocol

Step 2: Configure MCP Server Fill in the MCP configuration:

  • Name: Bedrock Knowledge Base Retrieval
  • Description: Amazon Bedrock Knowledge Base retrieval with natural language queries
  • MCP Server Endpoint: Paste your GatewayUrl from CDK deployment outputs
  • Click Next

Step 3: Configure Authentication

  1. For Authentication, select Service Authentication
  2. Keep Service-to-service OAuth within the Authentication type field

  3. Fill in the authentication values from your CDK deployment outputs:

  4. Client ID → Paste your ClientId (ensure no leading/trailing spaces)

  5. Client Secret → Paste your ClientSecret (ensure no leading/trailing spaces)
  6. Token URL → Paste your CognitoTokenUrl

Step 4: Complete Setup

  1. Click Create and Continue
  2. Select Next
  3. Select Next

Usage in QuickSuite

"List all available knowledge bases"
"Search for AWS Lambda best practices in my knowledge base"
"Find documents about data encryption with reranking enabled"
"Query kb-12345 about compliance requirements"

Troubleshooting

MCP Authentication Issues:

  • Verify OAuth2 credentials in QuickSuite MCP Actions
  • Check Cognito token endpoint configuration
  • Ensure client secret is correctly copied

Knowledge Base Access:

  • Verify Amazon Bedrock KB exists and is accessible
  • Check IAM permissions for Amazon Bedrock services
  • Confirm KB indexing is complete

AgentCore Gateway:

  • Monitor AgentCore Gateway throttling limits
  • Check Lambda timeout and memory settings
  • Review CORS configuration for QuickSuite

Documentation

License

This library is licensed under the MIT-0 License.