Amazon Bedrock Knowledge Base MCP Server
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- FlicenseNot gradedqualityBmaintenanceEnables to build and query a knowledge base with retrieval-augmented generation, supporting document ingestion, hybrid search, and live data integration from external APIs via MCP tools.1-
- AlicenseNot gradedqualityCmaintenanceEnables AI assistants to query documents in a Bedrock Knowledge Base through the MCP protocol, with tools for semantic search and agentic retrieval.MIT
- AlicenseAqualityDmaintenanceEnables creation and querying of knowledge bases using Google's Gemini API File Search feature, allowing AI applications to upload documents and retrieve information through RAG (Retrieval-Augmented Generation).3106MIT
- AlicenseNot gradedqualityCmaintenanceEnables querying, listing, and summarizing personal knowledge base documents using RAG with hybrid search and LLM.MIT
- FlicenseNot gradedqualityBmaintenanceConnects RAG knowledge bases to Claude Desktop and Claude Code, allowing retrieval-augmented generation from ingested documents.-
- AlicenseAqualityDmaintenanceEnables AI assistants to query and retrieve information from Amazon Bedrock Knowledge Base using the Retrieve API, returning search results with content, location, and relevance scores.1MIT
TDQS
Scored across 13 tools
Each tool has a distinct purpose with clear boundaries: create_bedrock_kb_role handles IAM role creation, create_s3_bucket and upload_document_to_s3 manage S3 infrastructure, create_knowledge_base and update_knowledge_base manage KB lifecycle, create_data_source configures data sources, start_ingestion_job and get_ingestion_job handle ingestion workflows, list_* tools provide read-only views, and retrieve performs querying. There is no functional overlap between tools.
All tools follow a consistent verb_noun naming pattern with snake_case: create_bedrock_kb_role, create_data_source, create_knowledge_base, create_s3_bucket, get_ingestion_job, get_knowledge_base, list_data_sources, list_knowledge_bases, list_s3_documents, retrieve, start_ingestion_job, update_knowledge_base, upload_document_to_s3. The pattern is perfectly uniform across all 13 tools.
With 13 tools, the set is well-scoped for managing Amazon Bedrock Knowledge Bases. It covers the full lifecycle: infrastructure setup (S3, IAM), KB CRUD operations, data source management, ingestion workflows, querying, and listing operations. Each tool serves a necessary purpose without redundancy.
The toolset provides comprehensive coverage for core KB workflows: create, read, update, list, and query operations are well-represented. Minor gaps include the lack of delete operations for knowledge bases, data sources, or S3 resources, and no tool to attach policies to the created IAM role. However, agents can still accomplish most tasks with the available tools.