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Introducing AWS MCP Servers for code assistants (Part 1)

AWS Machine Learning - AI

Were excited to announce the open source release of AWS MCP Servers for code assistants a suite of specialized Model Context Protocol (MCP) servers that bring Amazon Web Services (AWS) best practices directly to your development workflow. This post is the first in a series covering AWS MCP Servers.

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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

To achieve these goals, the AWS Well-Architected Framework provides comprehensive guidance for building and improving cloud architectures. This allows teams to focus more on implementing improvements and optimizing AWS infrastructure. This systematic approach leads to more reliable and standardized evaluations.

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Build and deploy a UI for your generative AI applications with AWS and Python

AWS Machine Learning - AI

AWS provides a powerful set of tools and services that simplify the process of building and deploying generative AI applications, even for those with limited experience in frontend and backend development. Choose the us-east-1 AWS Region from the top right corner. Choose Manage model access.

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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

For example, an AI-powered productivity tool for an ecommerce company might feature dedicated interfaces for different roles, such as content marketers and business analysts. This architecture workflow includes the following steps: A user submits a question through a web or mobile application. 70B and 8B.

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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning - AI

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. You can use AWS services such as Application Load Balancer to implement this approach. You can also bring your own customized models and deploy them to Amazon Bedrock for supported architectures.

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Harness the power of MCP servers with Amazon Bedrock Agents

AWS Machine Learning - AI

This is a problem that you can solve by using Model Context Protocol (MCP) , which provides a standardized way for LLMs to connect to data sources and tools. Today, MCP is providing agents standard access to an expanding list of accessible tools that you can use to accomplish a variety of tasks.

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Transcribe, translate, and summarize live streams in your browser with AWS AI and generative AI services

AWS Machine Learning - AI

Recognizing this need, we have developed a Chrome extension that harnesses the power of AWS AI and generative AI services, including Amazon Bedrock , an AWS managed service to build and scale generative AI applications with foundation models (FMs). The following diagram illustrates the architecture of the application.