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The **MCP Proxy for AWS** package provides two ways to connect AI applications to MCP servers on AWS:
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1.**Using it as a proxy** - It becomes a lightweight, client-side bridge between MCP clients (AI assistants like Claude Desktop, Amazon Q Developer CLI) and MCP servers on AWS. (See [MCP Proxy](#mcp-proxy))
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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](#mcp-proxy))
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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](#programmatic-access))
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### When Do You Need This Package?
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- You want to connect to **MCP servers on AWS** (e.g., using Amazon Bedrock AgentCore) that use AWS IAM authentication (SigV4) instead of OAuth
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- You're using MCP clients (like Claude Desktop, Amazon Q Developer CLI) that don't natively support AWS IAM authentication
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- You're using MCP clients (like Claude Desktop, Kiro CLI) that don't natively support AWS IAM authentication
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- You're building AI agents with popular frameworks like LangChain, Strands Agents, LlamaIndex, etc., that need to connect to MCP servers on AWS
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- You want to avoid building custom SigV4 request signing logic yourself
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## Which Feature Should I Use?
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**Use as a proxy if you want to:**
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- Connect MCP clients like Claude Desktop or Amazon Q Developer CLI to MCP servers on AWS with IAM credentials
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- Connect MCP clients like Claude Desktop or Kiro CLI to MCP servers on AWS with IAM credentials
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- Add MCP servers on AWS to your AI assistant's configuration
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- Use a command-line tool that runs as a bridge between your MCP client and AWS
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