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Enables AI assistants to execute AWS CLI commands and retrieve service documentation through the Model Context Protocol. It supports Unix pipes for output filtering and provides pre-defined prompt templates for common cloud management tasks.

Enables AI assistants to execute AWS CLI commands and access AWS documentation, resources, and prompt templates through the Model Context Protocol with support for Unix pipes and secure Docker-based deployment.

A read-only Model Context Protocol server that exposes over 60 AWS tools across services like EC2, S3, and IAM for AI agent interaction. It features multi-region support, resource caching, and audit logging to provide secure, AI-ready access to AWS infrastructure data.

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.

Enables Claude Desktop to interact with 57 AWS services using over 200 tools and local machine profiles. It supports multi-profile configurations and features a read-only safe mode by default to manage infrastructure like EC2, S3, and Lambda securely.

A Model Context Protocol server allowing Claude AI to interact with AWS resources through natural language, enabling users to query and manage AWS services without using the traditional AWS Console or CLI.

Provides read-only access to AWS resources including S3 buckets, EC2 instances, IAM users, and caller identity verification through the Model Context Protocol.

Provides a comprehensive suite of 76 tools for AWS cloud resource optimization, cost management, and infrastructure monitoring. It enables users to identify unused resources, analyze cost trends, right-size capacity, and maintain security compliance through natural language.

Enables interaction with AWS S3 storage through bucket operations (create, delete, list), object management (upload, download, delete, list), and bucket policy configuration using AWS credentials.

A unified MCP server for AWS that enables natural language infrastructure management, cross-service resource discovery, and dependency mapping. It features 30 intelligent tools for cost optimization, incident investigation, and multi-account operations protected by a robust safety system.

Orchestrates multiple AWS security services to provide comprehensive security assessments, threat analysis, and multi-framework compliance monitoring. It enables users to perform automated remediation recommendations and incident investigations through a unified Model Context Protocol interface.

Aws Serverless MCP

MCP Server implementation with AWS Serverless services.

A containerized Model Context Protocol server that enables using natural language to develop AWS infrastructure with Terraform, offering best practices guidance, security scanning with Checkov, and access to AWS provider documentation.

This server provides guidance and recommendations based on AWS's Well-Architected Framework for cloud architectures, enabling analysis and review focused on operational excellence, security, reliability, performance efficiency, cost optimization, and sustainability.

Enables interaction with Azure AI Foundry services including model exploration and deployment, knowledge management through AI Search, evaluation of text and agents, and fine-tuning operations. Provides unified access to Azure's AI capabilities through natural language commands.

Enables interaction with Azure AI Foundry services through a unified interface for model exploration and deployment, knowledge indexing and search, AI evaluation, and fine-tuning operations. Supports both GitHub token-based model testing and full Azure deployment workflows.

Enables interaction with Azure AI Foundry services for model exploration, deployment, and performance evaluation. It provides tools for managing knowledge bases via AI Search Service, executing fine-tuning jobs, and orchestrating AI agents through natural language.

Enables text-to-image generation and image editing using Azure AI Foundry models. Supports generating high-quality images from text descriptions and modifying existing images through natural language prompts.

Exposes backend APIs through Azure API Management as an MCP server to enable AI assistants to interact with product catalogs and order systems. It provides standardized tools for searching products, retrieving details, and managing orders via the Model Context Protocol.

Enables natural language exploration of Azure environments by generating and executing KQL queries against Azure Resource Graph. Supports multi-tenant configurations, subscription scoping, and provides direct access to Azure resource information through conversational interactions.