"AWS Lambda" matching MCP servers:

Enables Claude to interact with core AWS services like S3, EC2, RDS, and CloudWatch, along with a generic SDK wrapper for any AWS operation. It also supports cost monitoring and optional vector store capabilities for document ingestion and search.

Provides semantic search over AWS Cloudscape Design System documentation using natural language queries, enabling AI assistants to efficiently find and retrieve component documentation with token-efficient responses.

An MCP server for semantic search and retrieval of indexed Slack messages stored in Qdrant using Cohere reranking via AWS Bedrock. It enables users to search through Slack history, retrieve full message threads, and access channel or user statistics through natural language.

Enables MCP-compatible clients to search a shared ChromaDB-backed PDF document store and generate grounded, citation-aware answers through AWS Bedrock, without calling the REST API.

A vector search system that enables semantic retrieval of document chunks using MongoDB Atlas Vector Search and Voyage AI embeddings, allowing users to search documents by meaning rather than just keywords.

Provides AI agents with database-like operations over LanceDB with automatic BGE-M3 multilingual embedding generation, enabling semantic search, CRUD operations, and safe schema migrations across structured data.