Buat agen yang menggunakan AgentCore gateway Anda
Setelah membuat dan menguji gateway Anda, Anda dapat membuat dan menghubungkan agen AI ke gateway Anda. Agen yang terhubung ke gateway Anda dapat memanggil alat di gateway dan menggunakan model Amazon Bedrock untuk menanggapi kueri.
Untuk mempelajari cara membuat agen, menghubungkannya ke gateway, dan memanggilnya untuk menjawab pertanyaan, pilih salah satu metode berikut:
contoh
- Strands
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from strands import Agent from strands.models import BedrockModel from strands.tools.mcp.mcp_client import MCPClient from mcp.client.streamable_http import streamablehttp_client def _invoke_agent( bedrock_model, mcp_client, prompt ): with mcp_client: tools = mcp_client.list_tools_sync() agent = Agent( model=bedrock_model, tools=tools ) return agent(prompt) def _create_streamable_http_transport(headers=None): url = {gatewayUrl} access_token = {AccessToken} headers = {**headers} if headers else {} headers["Authorization"] = f"Bearer {access_token}" return streamablehttp_client( url, headers=headers ) def _get_bedrock_model(model_id): return BedrockModel( inference_profile_id=model_id, temperature=0.0, streaming=True, ) mcp_client = MCPClient(_create_streamable_http_transport) if __name__ == "__main__": user_prompt = "What orders do I have?" _response = _invoke_agent( bedrock_model=_get_bedrock_model("us.anthropic.claude-sonnet-4-20250514-v1:0"), mcp_client=mcp_client, prompt=user_prompt ) print(_response)
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- LangGraph
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from mcp import ClientSession from mcp.client.streamable_http import streamablehttp_client from langgraph.prebuilt import create_react_agent from langchain_mcp_adapters.tools import load_mcp_tools # Replace with actual values and the Amazon Bedrock model of your choice gateway_url = "${GatewayUrl}" access_token = "${AccessToken}" model = ChatBedrock(model_id="anthropic.claude-3-sonnet-20240229-v1:0", region_name="us-west-2") async with streamablehttp_client(gateway_url, headers={"Authorization": f"Bearer {access_token}"}) as (read, write, _): async with ClientSession(read, write) as session: # Initialize the connection await session.initialize() # Get tools tools = await load_mcp_tools(session) agent = create_react_agent(model, tools) math_response = await agent.ainvoke({"messages": "what's (3 + 5) x 12?"})
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- Claude Code
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#!/bin/bash # Script to add MCP server to Claude # Server configuration SERVER_NAME=${ServerName} # Write your server name GATEWAY_MCP_SERVER_URL=${GatewayUrl} # The gateway MCP URL AUTH_TOKEN=${AuthToken} # Claude authentication token echo "Adding MCP server to Claude..." echo "Server Name: $SERVER_NAME" echo "Server URL: $SERVER_URL" echo "" # Add the MCP server claude mcp add "$SERVER_NAME" "$GATEWAY_MCP_SERVER_URL" \ --transport http \ --header "Authorization: Bearer $AUTH_TOKEN" # Check if the command was successful if [ $? -eq 0 ]; then echo "MCP server added successfully!" echo "" echo "You can now check mcp server health with: claude mcp list" else echo "Failed to add MCP server" exit 1 fi
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Cari alat gateway
Aturan gateway