"Information about Amazon (company or rainforest)" matching MCP servers:

A high-performance Model Context Protocol (MCP) server that provides seamless integration with Amazon DataZone services. This server enables AI assistants and applications to interact with Amazon DataZone APIs through a standardized interface.

Provides access to Amazon Bedrock's Nova Canvas model for AI image generation.

An MCP server that enables AI assistants to interact with Amazon Connect contact centers, providing 88 tools, 91 configuration templates, and multi-region support.

An MCP server that lets an AI build hours of operation, queues, routing profiles, and real IVR flows from plain English, diagram them in chat, validate them with the platform's own flow validator, and prove them with simulated test calls. It is deliberately unable to go live on its own — no dialing, no number association, no deletes — so a human always makes the final connection.

A Model Context Protocol server that provides tools for accessing and managing AWS VPC Lattice information, allowing users to list sources and retrieve sample prompts related to AWS networking documentation.

Auto-generates MCP tools for all Amazon DataZone API operations, enabling natural language management of SageMaker Catalog resources.

This read-only MCP Server allows you to connect to Amazon S3 data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

Enables AI applications to interact with Amazon Advertising API through the Model Context Protocol. Supports campaign management, performance reporting, audience targeting, and comprehensive advertising operations across Amazon's advertising ecosystem.

Enables querying Amazon Neptune databases and analytics graphs using openCypher or Gremlin. It provides tools for executing queries, retrieving graph schemas, and monitoring connection status.

Send email through your own Amazon SES account, and check domain verification, the suppression list and sandbox status. Works with any SES account; Wraps adds send history and delivery events.

Enables management of Amazon Bedrock Knowledge Bases including creation, data source configuration, document ingestion, and RAG (Retrieval-Augmented Generation) queries with support for multiple embedding models and custom parsing/chunking strategies.

Enables access to Amazon Managed Prometheus workspaces through natural language queries. Supports listing workspaces, executing PromQL queries, and retrieving workspace details and metrics with AWS authentication.

Enables AI agents to manage RabbitMQ message brokers through admin APIs, supporting multiple brokers, OAuth authentication, and mutative tools.

Exposes existing AWS Lambda functions as MCP tools so AI agents can read and manage orders. Cognito-issued tokens and policy checks control which agents may call data-changing operations.

An MCP server for generating videos through Amazon Nova Reel 1.1 using AWS Bedrock, providing asynchronous video generation with comprehensive prompting guidelines and multiple transport methods.

Provides a private, managed instance of the official GitHub MCP server hosted on Amazon Bedrock AgentCore with Okta authentication. It allows developers to securely interact with GitHub through MCP-compatible IDEs over a private AWS infrastructure.

A proof-of-concept implementation that enables Amazon Bedrock AgentCore to interact with AWS Lambda functions and REST APIs through the Model Context Protocol. It provides a gateway for protocol translation and supports direct server implementation using the FastMCP framework.

Provides tools to validate SageMaker workloads against the six pillars of the AWS Well-Architected Framework, returning findings with severity levels and recommendations.

Enables natural-language querying and analysis of AWS spending and model-invocation usage, including detailed breakdowns by service, region, account, day, and instance type.

Enables natural-language queries of AWS spend and Bedrock usage data, providing detailed breakdowns by service, region, account, user, instance type, and model, including cross-account cost analysis.

Enables users to query and visualize AWS spend and Amazon Bedrock usage data through natural language, including EC2 and service cost breakdowns and Bedrock usage by region, user, and model.

Enables natural-language analysis of AWS spend through Cost Explorer and Amazon Bedrock usage via CloudWatch model invocation logs, with breakdowns by service, region, model, user, day, and instance type. It also supports cross-account cost retrieval and local or remote MCP transports.

Enables users to query AWS spend data and Amazon Bedrock usage from CloudWatch model invocation logs through natural language. Supports detailed cost breakdowns by service, region, day, and instance type, including cross-account AWS spend retrieval.

Enables users to query AWS spending and Amazon Bedrock usage in natural language through MCP clients, with breakdowns by service, region, day, model, and user, plus optional cross-account access.

Enables users to query and analyze cloud spending, EC2 cost breakdowns, service-level spend, and model usage logs through natural-language interactions. It also supports cross-account spend retrieval when configured.

Enables agents to retrieve and analyze cloud spending and model usage data, including service, region, instance-type, user, and model breakdowns.

Enables querying AWS Cost Explorer spend data and Amazon Bedrock model invocation logs through CloudWatch in natural language. Supports EC2, Bedrock, and cross-account cost analysis via local or remote MCP transports.

Enables querying AWS spend data via Cost Explorer and Amazon Bedrock usage data from CloudWatch logs using natural language. Supports cross-account access, local and remote deployment, and integration with Claude Desktop and LangGraph agents.

Enables users to analyze AWS spend and Bedrock model usage through natural-language queries, including EC2 costs, service spend reports, and breakdowns by region, model, and user.

Enables users to query AWS Cost Explorer spend data and Amazon Bedrock usage data from CloudWatch model invocation logs through natural language, including EC2 breakdowns, service spend reports, and detailed cost data by day, region, service, and instance type.