Simple Agentcore

简单代理核心示例

在Amazon Bedrock AgentCore上部署代理和MCP服务器的简单示例。

目录

simple-agent/          - HTTP agent on AgentCore Runtime (tested, working)
simple-a2a-agent/      - A2A protocol agent on AgentCore Runtime (tested, working)
simple-mcp/            - MCP server on AgentCore Gateway (tested, working)

先决条件

• Python 3.11+
• 配置了访问Amazon Bedrock AgentCore的AWS凭据
• uv 已安装包管理器

设置

uv sync

用法

代理名称必须以字母开头，并且只能包含字母、数字和下划线（没有连字符）。

简单代理/（HTTP代理）

支持两种身份验证模式：IAM（SigV4，默认）和Cognito（JWT承载令牌）。

cd simple-agent

# Deploy with IAM auth (default)
uv run python deploy_agent.py --agent-name my_simple_agent --region us-east-1

# Deploy with Cognito auth (auto-creates User Pool, App Client, test user)
uv run python deploy_agent.py --agent-name my_simple_agent --region us-east-1 --auth cognito

# Invoke with IAM auth
uv run python deploy_agent.py --agent-name my_simple_agent --region us-east-1 --invoke-only --prompt "What is 42 * 17?"

# Invoke with Cognito auth (auto-refreshes bearer token)
uv run python deploy_agent.py --agent-name my_simple_agent --region us-east-1 --auth cognito --invoke-only --prompt "What is 42 * 17?"

# Setup Cognito only (saves config to .cognito_config.json)
uv run python deploy_agent.py --agent-name my_simple_agent --region us-east-1 --setup-cognito

# Check status
uv run python deploy_agent.py --agent-name my_simple_agent --region us-east-1 --status-only

# Refresh Cognito token only (standalone script, saves to .token)
./get_token.sh

# Delete agent and Cognito resources
uv run python deploy_agent.py --agent-name my_simple_agent --region us-east-1 --delete

simple-a2a-agent/（a2a代理）

相同的计算器代理，但使用A2A协议。这使得代理卡发现和代理到代理的通信成为可能。使用单独的 client.py 用于调用（A2A代理需要A2A格式的消息，而不是启动器工具包的invoke方法）。

这 client.py 从自动读取代理ARN .bedrock_agentcore.yaml （在部署后创建），因此不需要硬编码。

cd simple-a2a-agent

# Full deployment (configure with A2A protocol, launch, wait for READY)
uv run python deploy_a2a_agent.py --agent-name my_a2a_agent --region us-east-1

# Invoke the agent via A2A client (reads ARN from .bedrock_agentcore.yaml)
uv run python client.py --prompt "What is 100 / 4 + 25?"

# Get the agent card (pretty printed, saved to agent_card.json)
uv run python client.py --agent-card-only

# Override agent ARN if needed
uv run python client.py --agent-arn  --prompt "What is 2 + 2?"

# Check status
uv run python deploy_a2a_agent.py --agent-name my_a2a_agent --region us-east-1 --status-only

# Delete the agent
uv run python deploy_a2a_agent.py --agent-name my_a2a_agent --region us-east-1 --delete

获取A2A代理卡

由于这是一个A2A代理，代理卡可以直接从运行时端点访问 /.well-known/agent.json。端点需要SigV4身份验证（纯 curl 将不起作用），因此使用 client.py 它自动处理身份验证：

cd simple-a2a-agent

# Fetch the agent card (handles SigV4 auth, saves to agent_card.json)
uv run python client.py --agent-card-only

代理卡URL从代理ARN导出，如下所示：

Runtime URL:    https://bedrock-agentcore.{region}.amazonaws.com/runtimes/{url-encoded-arn}/invocations/
Agent card URL: https://bedrock-agentcore.{region}.amazonaws.com/runtimes/{url-encoded-arn}/invocations/.well-known/agent.json

要打印已部署代理的完整URL，请执行以下操作：

python3 -c "
import yaml
from urllib.parse import quote
cfg = yaml.safe_load(open('.bedrock_agentcore.yaml'))
agent = cfg['agents'][cfg['default_agent']]
arn = agent['bedrock_agentcore']['agent_arn']
region = agent['aws']['region']
escaped = quote(arn, safe='')
runtime = f'https://bedrock-agentcore.{region}.amazonaws.com/runtimes/{escaped}/invocations/'
print(f'Agent endpoint:   {runtime}')
print(f'Agent card URL:   {runtime}.well-known/agent.json')
"

简单mcp/（网关上的mcp服务器）

将ipwho.is（免费HTTPS地理位置API）部署为具有Cognito JWT授权的AgentCore网关上的MCP服务器。

注意：与代理名称不同，网关名称使用连字符（不是下划线）。

cd simple-mcp

# Full deployment (IAM role, Cognito, Gateway, S3 upload, target, invoke)
uv run python deploy_mcp_server.py --gateway-name geo-mcp --region us-east-1

# Invoke only (requires prior deployment, reads saved deployment info)
uv run python deploy_mcp_server.py --gateway-name geo-mcp --region us-east-1 --invoke-only

# Custom prompt
uv run python deploy_mcp_server.py --gateway-name geo-mcp --region us-east-1 --invoke-only \
    --prompt "Where is IP address 1.1.1.1 located?"

# Delete and redeploy from scratch
uv run python deploy_mcp_server.py --gateway-name geo-mcp --region us-east-1 --delete
uv run python deploy_mcp_server.py --gateway-name geo-mcp --region us-east-1

# Delete all resources (gateway, credential provider, Cognito, IAM role)
uv run python deploy_mcp_server.py --gateway-name geo-mcp --region us-east-1 --delete

# Refresh Cognito token only (standalone script)
./get_token.sh

生成的文件（全部为gitignored）

部署后或 --invoke-only，生成以下文件 simple-mcp/:

使用curl测试MCP服务器

MCP协议使用HTTP上的JSON-RPC。在运行这些命令之前，您需要一个有效的令牌。

cd simple-mcp

# Refresh token first (tokens expire after ~1 hour)
./get_token.sh

# Set variables
GW_URL=$(python3 -c "import json;print(json.load(open('.deployment_info.json'))['gateway_url'])")
TOKEN=$(cat .token)

# Initialize MCP session and save session ID
curl -s -X POST "$GW_URL" \
    -H "Authorization: Bearer $TOKEN" \
    -H "Content-Type: application/json" \
    -d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-03-26","capabilities":{},"clientInfo":{"name":"curl","version":"1.0"}}}' \
    -D /tmp/mcp_headers > /dev/null
SESSION_ID=$(grep -i mcp-session-id /tmp/mcp_headers | tr -d '\r' | awk '{print $2}')

# List available tools
curl -s -X POST "$GW_URL" \
    -H "Authorization: Bearer $TOKEN" \
    -H "Content-Type: application/json" \
    -H "Mcp-Session-Id: $SESSION_ID" \
    -d '{"jsonrpc":"2.0","id":2,"method":"tools/list","params":{}}' | python3 -m json.tool

# Call a tool (geolocation lookup for 8.8.8.8)
curl -s -X POST "$GW_URL" \
    -H "Authorization: Bearer $TOKEN" \
    -H "Content-Type: application/json" \
    -H "Mcp-Session-Id: $SESSION_ID" \
    -d '{"jsonrpc":"2.0","id":3,"method":"tools/call","params":{"name":"geolocation___getGeolocationByIp","arguments":{"ipAddress":"8.8.8.8"}}}' | python3 -m json.tool

建筑

HTTP代理（简单代理/）

User -> deploy_agent.py -> AgentCore Runtime -> BedrockAgentCoreApp -> Strands Agent + Calculator

A2A代理（简单-A2A-Agent/）

client.py (SigV4) -> AgentCore Runtime -> A2AServer (FastAPI:9000) -> Strands Agent + Calculator
                                                    |
                                         /.well-known/agent-card.json

MCP服务器（简单MCP/）

User -> deploy_mcp_server.py -> Cognito (JWT) -> AgentCore Gateway (MCP) -> ipwho.is