A tool for querying AWS cost data and Bedrock usage logs via the MCP protocol

A reference project implementing the Model Context Protocol (MCP), providing a standard for tool calls between LLMs and applications, including local and remote call implementations, and integrating AWS Bedrock and Claude 3.7.

This project demonstrates a serverless MCP (Model Context Protocol) tool implementation based on AWS Lambda, including a Python server - side and a TypeScript client, supporting streaming HTTP communication. The server - side simplifies the MCP tool development process, has built - in session state management, and demonstrates integration with Amazon Bedrock.

This project demonstrates how to integrate the conversational AI capabilities of AWS Bedrock with relational databases through the MCP server architecture to achieve the function of querying databases in natural language.

A command-line tool and API for analyzing AWS Bedrock usage logs through Anthropic's MCP protocol, providing functions such as model usage statistics, user analysis, and natural language query.

This project is an AWS Bedrock Guardrails management server that provides functions for creating, editing, deleting, and exporting guardrails (including all policy types), and supports exporting configurations as Terraform files.

An MCP server project based on the Spring AI framework, using the Sync SSE transmission protocol, integrating the AWS Bedrock service, and utilizing PostgreSQL for vector storage.

A knowledge base search MCP server project based on AWS Bedrock and Cloudflare Workers, supporting AI assistants to search for document content through the protocol.

A guide to setting up MCP servers for AWS database services, supporting integration of multiple database types with Amazon Bedrock models

This project is an AWS cost analysis tool based on the Anthropic MCP protocol, providing a natural language interaction interface through the Claude model. It can query AWS Cost Explorer and Bedrock model call log data, and supports local and remote deployment.