概述

MCP 代理 for AWS 包提供了两种方式将 AI 应用连接到 AWS 上的 MCP 服务器：

1. 将其作为代理 - 它成为MCP客户端（如Claude Desktop、Kiro CLI等AI助手）与AWS上的MCP服务器之间的轻量级客户端桥梁。（参见MCP代理）
2. 将其用作库 - 通过程序方式将流行的AI代理框架（如LangChain、LlamaIndex、Strands Agents等）连接到AWS上的MCP服务器。（参见程序访问）

你什么时候需要这个包裹？

• 您希望连接到使用 AWS IAM 认证（SigV4）而非 OAuth 的 **MCP 服务器（例如 Amazon Bedrock AgentCore）
• 你使用的是不原生支持 AWS IAM 认证的 MCP 客户端（如 Claude Desktop、Kiro CLI）
• 你正在构建使用流行框架如LangChain、Strands Agents、LlamaIndex等的AI代理，这些框架需要连接到AWS上的MCP服务器
• 你想避免自己构建自定义的SigV4请求签名逻辑

这个包裹的帮助

问题： 官方MCP规范支持基于OAuth的认证，但AWS上的MCP服务器也可以使用AWS IAM认证（SigV4）。

MCP Proxy for AWS

Overview

The MCP Proxy for AWS package provides two ways to connect AI applications to MCP servers on AWS:

1. Using it as a proxy - It becomes a lightweight, client-side bridge between MCP clients (AI assistants like Claude Desktop, Kiro CLI) and MCP servers on AWS. (See MCP Proxy)
2. Using it as a library - Programmatically connect popular AI agent frameworks (LangChain, LlamaIndex, Strands Agents, etc.) to MCP servers on AWS. (See Programmatic Access)

When Do You Need This Package?

• You want to connect to MCP servers on AWS (e.g., using Amazon Bedrock AgentCore) that use AWS IAM authentication (SigV4) instead of OAuth
• You’re using MCP clients (like Claude Desktop, Kiro CLI) that don’t natively support AWS IAM authentication
• You’re building AI agents with popular frameworks like LangChain, Strands Agents, LlamaIndex, etc., that need to connect to MCP servers on AWS
• You want to avoid building custom SigV4 request signing logic yourself

How This Package Helps

The Problem: The official MCP specification supports OAuth-based authentication, but MCP servers on AWS can also use AWS IAM authentication (SigV4). Standard MCP clients don’t know how to sign requests with AWS credentials.

The Solution: This package bridges that gap by:

• Handling SigV4 authentication automatically - Uses your local AWS credentials (from AWS CLI, environment variables, or IAM roles) to sign all MCP requests using SigV4
• Providing seamless integration - Works with existing MCP clients and frameworks
• Eliminating custom code - No need to build your own MCP client with SigV4 signing logic

Which Feature Should I Use?

Use as a proxy if you want to:

• Connect MCP clients like Claude Desktop or Kiro CLI to MCP servers on AWS with IAM credentials
• Add MCP servers on AWS to your AI assistant’s configuration
• Use a command-line tool that runs as a bridge between your MCP client and AWS

→ Install mcp-proxy-for-aws-cli, the version-pinned CLI distribution: it freezes the entire dependency tree to tested versions. See MCP Proxy.

Use as a library if you want to:

• Build AI agents programmatically using popular frameworks like LangChain, Strands Agents, or LlamaIndex
• Integrate AWS IAM-secured MCP servers directly into your Python applications
• Have fine-grained control over the MCP session lifecycle in your code

→ Install mcp-proxy-for-aws, the library distribution: it keeps loose, co-resolvable dependency ranges so it resolves alongside your own dependencies. See Programmatic Access.

Prerequisites

• Install Python 3.10+
• Install the uv package manager