Agent RegistryにA2Aエージェントを登録してStrands Agentsから動的に呼び出してみた

git clone https://github.com/yuu551/a2a-agentcore-strands.git
cd a2a-agentcore-strands
uv sync

.
├── register_a2a.py             # A2A Agent CardをRegistryへ登録
├── registry_a2a_loader.py      # RegistryからA2AClientToolProviderを組み立てる
├── a2a_client.py               # ローカルからオーケストレーターを動かす
├── invoke_orchestrator.py      # Runtime上のオーケストレーターをSSEで呼び出す
├── sigv4_auth.py               # httpx用 SigV4 Auth
└── terraform/
    ├── versions.tf
    ├── variables.tf
    ├── iam.tf
    ├── runtime.tf
    ├── outputs.tf
    └── agent/
        ├── calculator/         # A2A: 計算エージェント
        │   ├── server.py
        │   ├── Dockerfile
        │   └── requirements.txt
        ├── weather/            # A2A: 天気エージェント
        │   ├── server.py
        │   ├── Dockerfile
        │   └── requirements.txt
        └── orchestrator/       # HTTP: オーケストレーター
            ├── server.py
            ├── registry_a2a_loader.py  # ルートからコピー
            ├── sigv4_auth.py           # ルートからコピー
            ├── Dockerfile
            └── requirements.txt

from __future__ import annotations

import os

import uvicorn
from strands import Agent
from strands.models import BedrockModel
from strands.multiagent.a2a import A2AServer
from strands_tools.calculator import calculator

MODEL_ID = "us.anthropic.claude-haiku-4-5-20251001-v1:0"
REGION = os.environ.get("AWS_REGION", "us-east-1")
RUNTIME_URL = os.environ.get("AGENTCORE_RUNTIME_URL", "http://127.0.0.1:9000/")

model = BedrockModel(model_id=MODEL_ID, region_name=REGION)

agent = Agent(
    name="計算エージェント",
    description="四則演算・代数・微積分・記号計算を行うエージェントです。",
    model=model,
    tools=[calculator],
    callback_handler=None,
)

server = A2AServer(
    agent=agent,
    host="0.0.0.0",
    port=9000,
    http_url=RUNTIME_URL,
    serve_at_root=True,
)

app = server.to_fastapi_app()

if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=9000)

from __future__ import annotations

import os

import uvicorn
from strands import Agent, tool
from strands.models import BedrockModel
from strands.multiagent.a2a import A2AServer

MODEL_ID = "us.anthropic.claude-haiku-4-5-20251001-v1:0"
REGION = os.environ.get("AWS_REGION", "us-east-1")
RUNTIME_URL = os.environ.get("AGENTCORE_RUNTIME_URL", "http://127.0.0.1:9000/")

_MOCK_WEATHER = {
    "tokyo": {"condition": "Sunny", "temperature_c": 22, "humidity": 55},
    "osaka": {"condition": "Cloudy", "temperature_c": 20, "humidity": 65},
    "sapporo": {"condition": "Snowy", "temperature_c": -2, "humidity": 80},
    "fukuoka": {"condition": "Rainy", "temperature_c": 18, "humidity": 75},
    "naha": {"condition": "Sunny", "temperature_c": 27, "humidity": 70},
}

@tool
def get_weather(city: str) -> dict:
    """日本の都市の現在の天気情報を返します。対応都市: Tokyo, Osaka, Sapporo, Fukuoka, Naha。"""
    data = _MOCK_WEATHER.get(city.strip().lower())
    if data is None:
        return {"error": f"Unknown city: {city}. Supported: {list(_MOCK_WEATHER)}"}
    return {"city": city, **data}

model = BedrockModel(model_id=MODEL_ID, region_name=REGION)

agent = Agent(
    name="天気エージェント",
    description="日本の主要都市の現在の天気情報を返すエージェントです。",
    model=model,
    tools=[get_weather],
    callback_handler=None,
)

server = A2AServer(
    agent=agent,
    host="0.0.0.0",
    port=9000,
    http_url=RUNTIME_URL,
    serve_at_root=True,
)

app = server.to_fastapi_app()

if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=9000)

FROM --platform=linux/arm64 public.ecr.aws/docker/library/python:3.12-slim

WORKDIR /app

COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

COPY server.py .

EXPOSE 9000

CMD ["python", "server.py"]

strands-agents[a2a]>=1.36.0
strands-agents-tools>=0.5.0
fastapi>=0.115.0
uvicorn>=0.32.0

locals {
  agents = {
    calculator = { source_dir = "${path.module}/agent/calculator" }
    weather    = { source_dir = "${path.module}/agent/weather" }
  }
}

resource "aws_ecr_repository" "calculator" {
  name                 = "${var.project_name}-calculator-${random_string.suffix.result}"
  image_tag_mutability = "MUTABLE"
  force_delete         = true
}

resource "aws_ecr_repository" "weather" {
  name                 = "${var.project_name}-weather-${random_string.suffix.result}"
  image_tag_mutability = "MUTABLE"
  force_delete         = true
}

resource "null_resource" "calculator_build_push" {
  triggers = {
    dockerfile   = filemd5("${local.agents.calculator.source_dir}/Dockerfile")
    server       = filemd5("${local.agents.calculator.source_dir}/server.py")
    requirements = filemd5("${local.agents.calculator.source_dir}/requirements.txt")
  }

  provisioner "local-exec" {
    working_dir = local.agents.calculator.source_dir
    command     = <<-EOT
      aws ecr get-login-password --region ${data.aws_region.current.region} | \
        docker login --username AWS --password-stdin ${aws_ecr_repository.calculator.repository_url}
      docker buildx build --platform linux/arm64 \
        -t ${aws_ecr_repository.calculator.repository_url}:latest --push .
    EOT
  }

  depends_on = [aws_ecr_repository.calculator]
}

# weather_build_push も同じ構造なので省略

resource "aws_bedrockagentcore_agent_runtime" "calculator" {
  agent_runtime_name = replace("${var.project_name}_calculator_${random_string.suffix.result}", "-", "_")
  description        = "Calculator A2A server"
  role_arn           = aws_iam_role.agent_runtime.arn

  agent_runtime_artifact {
    container_configuration {
      container_uri = "${aws_ecr_repository.calculator.repository_url}:latest"
    }
  }

  network_configuration {
    network_mode = "PUBLIC"
  }

  protocol_configuration {
    server_protocol = "A2A"
  }

  depends_on = [
    null_resource.calculator_build_push,
    aws_iam_role_policy.runtime_ecr,
    aws_iam_role_policy.runtime_logs,
    aws_iam_role_policy.runtime_bedrock,
  ]
}

# aws_bedrockagentcore_agent_runtime.weather も同じ構造なので省略

resource "aws_iam_role" "agent_runtime" {
  name = "${var.project_name}-runtime-${random_string.suffix.result}"

  assume_role_policy = jsonencode({
    Version = "2012-10-17"
    Statement = [{
      Effect    = "Allow"
      Action    = "sts:AssumeRole"
      Principal = { Service = "bedrock-agentcore.amazonaws.com" }
      Condition = {
        StringEquals = { "aws:SourceAccount" = data.aws_caller_identity.current.account_id }
      }
    }]
  })
}

resource "aws_iam_role_policy" "runtime_bedrock" {
  name = "bedrock-invoke"
  role = aws_iam_role.agent_runtime.id

  policy = jsonencode({
    Version = "2012-10-17"
    Statement = [{
      Effect = "Allow"
      Action = ["bedrock:InvokeModel", "bedrock:InvokeModelWithResponseStream"]
      Resource = "*"
    }]
  })
}

# runtime_ecr / runtime_logs は省略。詳細はGitHubのリポジトリを参照してください

output "calculator_runtime_arn" {
  value = aws_bedrockagentcore_agent_runtime.calculator.agent_runtime_arn
}

output "weather_runtime_arn" {
  value = aws_bedrockagentcore_agent_runtime.weather.agent_runtime_arn
}

cd terraform
terraform init
terraform apply

from __future__ import annotations

import boto3
import httpx
from botocore.auth import SigV4Auth
from botocore.awsrequest import AWSRequest

class SigV4HttpxAuth(httpx.Auth):
    requires_request_body = True

    def __init__(self, region: str, service: str = "bedrock-agentcore") -> None:
        credentials = boto3.Session().get_credentials()
        if credentials is None:
            raise RuntimeError("No AWS credentials found.")
        self._signer = SigV4Auth(credentials, service, region)

    def auth_flow(self, request: httpx.Request):
        aws_request = AWSRequest(
            method=request.method,
            url=str(request.url),
            data=request.content,
            headers=dict(request.headers),
        )
        self._signer.add_auth(aws_request)
        for key, value in aws_request.headers.items():
            request.headers[key] = value
        yield request

"""Register A2A agents (Calculator / Weather) to AWS Agent Registry."""
from __future__ import annotations

import json
import logging
import os
import time
from urllib.parse import quote

import boto3
import httpx

from sigv4_auth import SigV4HttpxAuth

logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s: %(message)s")
logger = logging.getLogger(__name__)

REGISTRY_ID = os.environ["AGENT_REGISTRY_ID"]
REGION = os.environ.get("AWS_REGION", "us-east-1")

def runtime_base_url(arn: str) -> str:
    return f"https://bedrock-agentcore.{REGION}.amazonaws.com/runtimes/{quote(arn, safe='')}/invocations"

def fetch_agent_card(base_url: str, auth: SigV4HttpxAuth) -> dict:
    card_url = f"{base_url}/.well-known/agent-card.json"
    response = httpx.get(card_url, auth=auth, timeout=30.0)
    response.raise_for_status()
    return response.json()

def wait_until_not(control, registry_id: str, record_id: str, transient: str, *, timeout: float = 30.0) -> str:
    deadline = time.monotonic() + timeout
    while True:
        status = control.get_registry_record(registryId=registry_id, recordId=record_id)["status"]
        if status != transient:
            return status
        if time.monotonic() > deadline:
            raise TimeoutError(f"record {record_id} stuck in {transient}")
        time.sleep(1.0)

def register(control, name: str, description: str, card: dict) -> str:
    created = control.create_registry_record(
        registryId=REGISTRY_ID,
        name=name,
        description=description,
        recordVersion="1.0",
        descriptorType="A2A",
        descriptors={"a2a": {"agentCard": {"inlineContent": json.dumps(card)}}},
    )
    record_id = created["recordArn"].rsplit("/", 1)[-1]
    logger.info("Created record %s (status=%s)", record_id, created["status"])

    wait_until_not(control, REGISTRY_ID, record_id, "CREATING")
    control.submit_registry_record_for_approval(registryId=REGISTRY_ID, recordId=record_id)
    status = wait_until_not(control, REGISTRY_ID, record_id, "SUBMITTING")
    logger.info("Record %s reached status %s", record_id, status)
    return record_id

def main() -> None:
    control = boto3.client("bedrock-agentcore-control", region_name=REGION)
    auth = SigV4HttpxAuth(region=REGION)

    targets = [
        ("calculator-a2a", "Calculator A2A agent (SymPy)", os.environ["CALCULATOR_RUNTIME_ARN"]),
        ("weather-a2a", "Weather A2A agent (mock for Japan cities)", os.environ["WEATHER_RUNTIME_ARN"]),
    ]

    for name, description, arn in targets:
        base = runtime_base_url(arn)
        card = fetch_agent_card(base, auth)
        logger.info("Fetched agent card for %s: %s", name, card["name"])
        record_id = register(control, name, description, card)
        print(f"{name}: {record_id}")

if __name__ == "__main__":
    main()

export AGENT_REGISTRY_ID="xxx"
export CALCULATOR_RUNTIME_ARN="$(cd terraform && terraform output -raw calculator_runtime_arn)"
export WEATHER_RUNTIME_ARN="$(cd terraform && terraform output -raw weather_runtime_arn)"
uv run python register_a2a.py

INFO: Fetched agent card for calculator-a2a: 計算エージェント
INFO: Created record ul4ncy9CGo0p (status=CREATING)
INFO: Record ul4ncy9CGo0p reached status APPROVED
INFO: Fetched agent card for weather-a2a: 天気エージェント
INFO: Created record vZspJcEwxhy5 (status=CREATING)
INFO: Record vZspJcEwxhy5 reached status APPROVED
calculator-a2a: ul4ncy9CGo0p
weather-a2a: vZspJcEwxhy5

"""Search AWS Agent Registry for A2A records and build A2AClientToolProvider."""
from __future__ import annotations

import json
import logging
from dataclasses import dataclass
from typing import Any

import boto3
from strands_tools.a2a_client import A2AClientToolProvider

from sigv4_auth import SigV4HttpxAuth

logger = logging.getLogger(__name__)

@dataclass
class RegistryA2ALoaderConfig:
    registry_id: str
    region_name: str = "us-east-1"
    max_results: int = 10

class RegistryA2ALoader:
    def __init__(self, config: RegistryA2ALoaderConfig) -> None:
        self._config = config
        self._client = boto3.client("bedrock-agentcore", region_name=config.region_name)

    def search(self, query: str) -> A2AClientToolProvider:
        response = self._client.search_registry_records(
            registryIds=[self._config.registry_id],
            searchQuery=query,
            maxResults=self._config.max_results,
            filters={"descriptorType": {"$eq": "A2A"}},
        )
        records = response.get("registryRecords") or []
        logger.info("Fetched %d A2A record(s) from registry", len(records))

        urls: list[str] = []
        for record in records:
            url = self._extract_url(record)
            if url:
                urls.append(url)
                logger.info("Loaded A2A: %s -> %s", record.get("name"), url[:80])

        auth = SigV4HttpxAuth(region=self._config.region_name)
        return A2AClientToolProvider(
            known_agent_urls=urls,
            httpx_client_args={"auth": auth},
        )

    @staticmethod
    def _extract_url(record: dict[str, Any]) -> str | None:
        descriptors = record.get("descriptors") or {}
        a2a_desc = descriptors.get("a2a") or {}
        card_json = (a2a_desc.get("agentCard") or {}).get("inlineContent")
        if not card_json:
            return None
        card = json.loads(card_json)
        return card.get("url")

"""Orchestrator Strands Agent that loads A2A tools from Agent Registry."""
from __future__ import annotations

import logging
import os

from strands import Agent
from strands.models import BedrockModel

from registry_a2a_loader import RegistryA2ALoader, RegistryA2ALoaderConfig

logging.basicConfig(level=logging.INFO, format="%(asctime)s %(name)s %(levelname)s: %(message)s")
logger = logging.getLogger(__name__)

MODEL_ID = "us.anthropic.claude-haiku-4-5-20251001-v1:0"

def main() -> None:
    region = os.environ.get("AWS_REGION", "us-east-1")

    config = RegistryA2ALoaderConfig(
        registry_id=os.environ["AGENT_REGISTRY_ID"],
        region_name=region,
    )
    loader = RegistryA2ALoader(config)
    provider = loader.search("calculator weather")

    model = BedrockModel(model_id=MODEL_ID, region_name=region)

    agent = Agent(
        model=model,
        tools=provider.tools,
        system_prompt=(
            "You are an orchestrator that delegates tasks to remote A2A agents. "
            "Use the A2A tools to send requests to the appropriate agent discovered from the registry."
        ),
    )

    user_input = (
        "東京の天気を教えてください。その後、現在の気温（摂氏）を華氏に変換してください（華氏 = 摂氏 × 9 / 5 + 32）。"
    )

    logger.info("Query: %s", user_input)
    result = agent(user_input)
    print("\n--- result ---")
    print(result.message)

if __name__ == "__main__":
    main()

AGENT_REGISTRY_ID="xxx" uv run python a2a_client.py

registry_a2a_loader INFO: Fetched 2 A2A record(s) from registry
registry_a2a_loader INFO: Loaded A2A: calculator-a2a -> https://bedrock-agentcore.us-east-1.amazonaws.com/runtimes/...
registry_a2a_loader INFO: Loaded A2A: weather-a2a -> https://bedrock-agentcore.us-east-1.amazonaws.com/runtimes/...
strands_tools.a2a_client INFO: Successfully discovered and cached agent card for (Weather)
strands_tools.a2a_client INFO: Sending message to (Weather)
strands_tools.a2a_client INFO: Successfully discovered and cached agent card for (Calculator)
strands_tools.a2a_client INFO: Sending message to (Calculator)

## 東京の天気情報
- 天気: 晴れ
- 気温: 22°C
- 湿度: 55%

## 気温の変換
摂氏22°C を華氏に変換：
計算式：華氏 = 摂氏 × 9 / 5 + 32
22 × 9 ÷ 5 + 32 = 71.6°F

したがって、東京の現在の気温 22°C は華氏では 71.6°F です！

from __future__ import annotations

import logging
import os

from bedrock_agentcore.runtime import BedrockAgentCoreApp
from strands import Agent
from strands.models import BedrockModel

from registry_a2a_loader import RegistryA2ALoader, RegistryA2ALoaderConfig

logging.basicConfig(level=logging.INFO, format="%(asctime)s %(name)s %(levelname)s: %(message)s")
logger = logging.getLogger(__name__)

MODEL_ID = "us.anthropic.claude-haiku-4-5-20251001-v1:0"
REGION = os.environ.get("AWS_REGION", "us-east-1")
REGISTRY_ID = os.environ["AGENT_REGISTRY_ID"]

app = BedrockAgentCoreApp()

@app.entrypoint
async def handler(payload: dict, context):
    query = payload.get("prompt")
    if not query:
        yield {"error": "`prompt` is required"}
        return

    search_query = payload.get("search_query", query)

    config = RegistryA2ALoaderConfig(registry_id=REGISTRY_ID, region_name=REGION)
    loader = RegistryA2ALoader(config)
    provider = loader.search(search_query)

    model = BedrockModel(model_id=MODEL_ID, region_name=REGION)
    agent = Agent(
        model=model,
        tools=provider.tools,
        system_prompt=(
            "You are an orchestrator that delegates tasks to remote A2A agents."
        ),
    )

    async for event in agent.stream_async(query):
        yield event

if __name__ == "__main__":
    app.run()

FROM --platform=linux/arm64 public.ecr.aws/docker/library/python:3.12-slim

WORKDIR /app

COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
RUN pip install --no-cache-dir aws-opentelemetry-distro==0.12.2

COPY server.py .
COPY registry_a2a_loader.py .
COPY sigv4_auth.py .

EXPOSE 8080

CMD ["opentelemetry-instrument", "python", "server.py"]

resource "aws_bedrockagentcore_agent_runtime" "orchestrator" {
  agent_runtime_name = replace("${var.project_name}_orchestrator_${random_string.suffix.result}", "-", "_")
  description        = "Orchestrator HTTP server calling A2A agents via Registry"
  role_arn           = aws_iam_role.orchestrator_runtime.arn

  agent_runtime_artifact {
    container_configuration {
      container_uri = "${aws_ecr_repository.orchestrator.repository_url}:latest"
    }
  }

  network_configuration {
    network_mode = "PUBLIC"
  }

  protocol_configuration {
    server_protocol = "HTTP"
  }

  environment_variables = {
    AGENT_REGISTRY_ID = var.agent_registry_id
  }
}

resource "aws_iam_role_policy" "orchestrator_invoke_runtime" {
  name = "invoke-a2a-runtime"
  role = aws_iam_role.orchestrator_runtime.id

  policy = jsonencode({
    Version = "2012-10-17"
    Statement = [{
      Effect = "Allow"
      Action = [
        "bedrock-agentcore:InvokeAgentRuntime",
        "bedrock-agentcore:InvokeAgentRuntimeForUser",
        "bedrock-agentcore:GetAgentCard",  # ← A2A Agent Card取得に必要
      ]
      Resource = [
        aws_bedrockagentcore_agent_runtime.calculator.agent_runtime_arn,
        "${aws_bedrockagentcore_agent_runtime.calculator.agent_runtime_arn}/runtime-endpoint/*",
        aws_bedrockagentcore_agent_runtime.weather.agent_runtime_arn,
        "${aws_bedrockagentcore_agent_runtime.weather.agent_runtime_arn}/runtime-endpoint/*",
      ]
    }]
  })
}

"""Invoke the Orchestrator Runtime and pretty-print the SSE stream."""
from __future__ import annotations

import json
import os
import sys

import boto3

REGION = os.environ.get("AWS_REGION", "us-east-1")

def stream_events(body: bytes):
    for chunk in body.decode("utf-8", errors="replace").split("\n\n"):
        chunk = chunk.strip()
        if not chunk.startswith("data:"):
            continue
        try:
            yield json.loads(chunk[5:].strip())
        except json.JSONDecodeError:
            continue

def pretty_print(body: bytes) -> None:
    tool_use: dict[str, dict] = {}
    for event in stream_events(body):
        if not isinstance(event, dict):
            continue
        ev = event.get("event") or {}

        if "contentBlockStart" in ev:
            tu = (ev["contentBlockStart"].get("start") or {}).get("toolUse")
            if tu:
                tool_use[tu["toolUseId"]] = {"name": tu.get("name"), "input": ""}
                print(f"\n[tool_call] {tu.get('name')}", flush=True)

        if "contentBlockDelta" in ev:
            delta = ev["contentBlockDelta"].get("delta") or {}
            if "text" in delta:
                sys.stdout.write(delta["text"])
                sys.stdout.flush()
            if "toolUse" in delta:
                frag = delta["toolUse"].get("input", "")
                for tu in tool_use.values():
                    tu["input"] += frag
                    break

        if "contentBlockStop" in ev:
            for tu in list(tool_use.values()):
                if tu["input"]:
                    try:
                        args = json.loads(tu["input"])
                        print(f"  args: {json.dumps(args, ensure_ascii=False)[:200]}", flush=True)
                    except json.JSONDecodeError:
                        pass
                    tu["input"] = ""

        if "messageStop" in ev:
            print(flush=True)

def main() -> None:
    arn = os.environ["ORCHESTRATOR_RUNTIME_ARN"]
    prompt = " ".join(sys.argv[1:]) or "東京の天気を教えて、気温を華氏に変換して。"
    search_query = os.environ.get("SEARCH_QUERY", "calculator weather")

    client = boto3.client("bedrock-agentcore", region_name=REGION)
    response = client.invoke_agent_runtime(
        agentRuntimeArn=arn,
        qualifier="DEFAULT",
        payload=json.dumps({"prompt": prompt, "search_query": search_query}).encode(),
        contentType="application/json",
    )
    pretty_print(response["response"].read())

if __name__ == "__main__":
    main()

export ORCHESTRATOR_RUNTIME_ARN="$(cd terraform && terraform output -raw orchestrator_runtime_arn)"
uv run python invoke_orchestrator.py "東京の天気を教えて、気温を華氏に変換して。"

東京の天気情報と気温の華氏変換をお手伝いします。まず、利用可能なエージェントを確認させてください。
[tool_call] a2a_list_discovered_agents

完璧です！天気エージェントと計算機エージェントが利用可能です。東京の天気情報を取得し、その後気温を華氏に変換します。
[tool_call] a2a_send_message
  args: {"message_text": "東京の現在の天気情報を教えてください。", "target_agent_url": "https://.../a2a_demo_weather_.../invocations/"}

素晴らしい！東京の天気情報を取得できました。次に、気温の22°Cを華氏に変換します。
[tool_call] a2a_send_message
  args: {"message_text": "22度セルシウスを華氏に変換してください。計算式は (22 * 9/5) + 32 です。", "target_agent_url": "https://.../a2a_demo_calculator_.../invocations/"}

完璧です！東京の天気情報と気温の華氏への変換が完了しました。

## 📍 東京の天気情報

**現在の天気：**
- **天気：** 晴れ（Sunny）
- **気温：** 22°C → **71.6°F（華氏）**
- **湿度：** 55%

良い天気が続いており、過ごしやすい気温のようですね。22度セルシウスは華氏では71.6度で、室温としては快適な温度です。

Fetched 2 A2A record(s) from registry
Loaded A2A: calculator-a2a -> https://bedrock-agentcore.us-east-1.amazonaws.com/...
Loaded A2A: weather-a2a -> https://bedrock-agentcore.us-east-1.amazonaws.com/...
Successfully discovered and cached agent card for ...weather...
Successfully discovered and cached agent card for ...calculator...
Sending message to ...weather...
Sending message to ...calculator...