{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/11"}],"enrichment":{"capability":"An MCP server that connects AI tools to Amazon Bedrock Knowledge Bases, enabling natural-language queries, result filtering by data source, and optional reranking of retrieved passages.","skillfed_tags":["mcp-server","aws-bedrock","rag"],"use_cases":["Integrate Bedrock Knowledge Bases into AI agents or chat applications so they can retrieve and cite domain-specific information in real time.","Query multiple knowledge bases from a single MCP client interface, filtering by data source to focus retrieval on specific document collections.","Improve search relevance by enabling Bedrock reranking on knowledge base results when available in your region.","Discover and explore all available knowledge bases and their data sources programmatically through an MCP server.","Build AI assistants that combine Bedrock models with your own knowledge bases for grounded, cited responses."],"what_it_does":"This is an MCP (Model Context Protocol) server that bridges AI tools and applications to Amazon Bedrock Knowledge Bases. It exposes Bedrock knowledge bases as discoverable resources with natural-language query capabilities, allowing AI models and agents to retrieve relevant passages, filter results by data source, and optionally rerank results for improved relevance. The package wraps boto3 calls to Bedrock behind an MCP interface, so it runs as a server process that MCP-compatible clients (Kiro, Cursor, VS Code, or other tools) connect to.\n\nThe server requires AWS credentials and IAM permissions to access Bedrock and your knowledge bases. It supports filtering knowledge bases by tag, querying with conversational language, and returning citation information alongside results. Reranking is optional and controlled via environment variable or per-query parameter; it requires additional IAM permissions and is only available in certain AWS regions. The package is actively maintained, supports Python 3.10\u20133.13, and has no known vulnerabilities.","worth_installing":"Yes, if you use Bedrock Knowledge Bases and need to expose them to AI tools via MCP. The package is actively maintained, has low install friction, permissive licensing, and zero known vulnerabilities. Install only if you have AWS credentials, appropriate IAM permissions, and at least one tagged knowledge base; otherwise, setup will fail at runtime."},"id":"awslabs-bedrock-kb-retrieval-mcp-server","links":{"html":"https://skillfed.io/packages/awslabs-bedrock-kb-retrieval-mcp-server","md":"https://skillfed.io/packages/awslabs-bedrock-kb-retrieval-mcp-server.md","pypi":"https://pypi.org/project/awslabs-bedrock-kb-retrieval-mcp-server/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-10","license_spdx":null,"license_treatment":"permissive","name":"awslabs.bedrock-kb-retrieval-mcp-server","python_support":"supports_current","summary":"An AWS Labs Model Context Protocol (MCP) server for Bedrock Knowledge Base Retrieval"},"popularity":{"monthly_downloads":82853,"position":14123,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.0.25"}