2nd/10_Wiki/Topic_Programming/Architecture/A2A.md

id, title, category, status, canonical_id, aliases, duplicate_of, source_trust_level, confidence_score, verification_status, tags, raw_sources, last_reinforced, github_commit, tech_stack

id	title	category	status	canonical_id	aliases	duplicate_of	source_trust_level	confidence_score	verification_status	tags	raw_sources	last_reinforced	github_commit	tech_stack
wiki-2026-0508-a2a	A2A (Agent-to-Agent Protocol)	10_Wiki/Topics	verified	self	Agent-to-Agent A2A Protocol Agent2Agent	none	A	0.9	applied	agents protocol interop anthropic mcp		2026-05-10	pending	language framework python anthropic-sdk

A2A (Agent-to-Agent Protocol)

매 한 줄

"매 agent 가 다른 agent 와 모델/벤더 차이 없이 task 를 위임/협상/결과 교환 하기 위한 open protocol." Google 이 2025 봄 announce, 2025-06 Linux Foundation 으로 stewardship 이전, 2026 현재 Anthropic / Microsoft / Salesforce 등 50+ 기업 adoption. 매 MCP (tool/data) 와 directly complementary — 매 A2A 는 agent ↔ agent, MCP 는 agent ↔ tool.

매 핵심

매 5 design principles

• Agentic by default: 매 agent autonomy 를 가정 (매 mere RPC 가 아님).
• Modality-agnostic: 매 text / audio / video / structured data 모두 transport.
• Built on web standards: HTTP + JSON-RPC 2.0 + SSE / WebSocket — 매 separate runtime 불필요.
• Secure by design: OAuth 2.1, 매 mTLS, 매 capability scoping.
• Long-running task aware: 매 minutes ~ days 의 async task — 매 polling + push-notification 모두 지원.

매 핵심 primitives

• AgentCard (/.well-known/agent.json): 매 agent 의 capability advertisement.
• Task: 매 unit of work — submitted → working → input-required → completed/failed/canceled.
• Message + Artifact: 매 conversation chunk + 매 final output.
• Streaming: SSE 로 매 partial token / 매 status update 전송.

매 응용

1. Cross-vendor agent orchestration (Claude → Gemini → in-house).
2. Specialist agent dispatch (legal, finance, code-review).
3. Marketplace 의 agent invocation.

💻 패턴

1) AgentCard 발행

{
  "name": "claude-research-agent",
  "version": "1.2.0",
  "url": "https://api.example.com/a2a",
  "capabilities": {
    "streaming": true,
    "pushNotifications": true,
    "stateTransitionHistory": true
  },
  "skills": [
    {"id": "deep-research", "description": "Multi-source web research", "inputModes": ["text"], "outputModes": ["text", "file"]}
  ],
  "auth": {"type": "oauth2.1", "scopes": ["task:submit"]}
}

2) Task 제출 (client agent)

import httpx, uuid

resp = httpx.post(
    "https://api.example.com/a2a/tasks/send",
    json={
        "jsonrpc": "2.0", "id": "1", "method": "tasks/send",
        "params": {
            "id": str(uuid.uuid4()),
            "message": {
                "role": "user",
                "parts": [{"type": "text", "text": "Summarize Q4 earnings of NVDA."}]
            }
        }
    },
    headers={"Authorization": f"Bearer {token}"}
)
task = resp.json()["result"]

3) SSE streaming 으로 partial result 수신

with httpx.stream("POST", url + "/tasks/sendSubscribe", json=req) as s:
    for line in s.iter_lines():
        if line.startswith("data:"):
            event = json.loads(line[5:])
            if event["type"] == "status": ...
            elif event["type"] == "artifact": print(event["artifact"]["parts"])

4) Push notification 등록 (long task)

httpx.post(url + "/tasks/pushNotification/set", json={
    "taskId": task["id"],
    "pushNotificationConfig": {
        "url": "https://my-app.com/a2a/webhook",
        "token": webhook_secret
    }
})

5) Server-side handler (FastAPI 예)

from fastapi import FastAPI
app = FastAPI()

@app.post("/a2a/tasks/send")
async def send(req: dict):
    task_id = req["params"]["id"]
    # 매 background worker 에게 dispatch
    await queue.put((task_id, req["params"]["message"]))
    return {"jsonrpc":"2.0","id":req["id"],"result":{"id":task_id,"status":{"state":"submitted"}}}

6) Multi-agent orchestration (A2A + MCP combo)

# Orchestrator agent: A2A 로 specialist 호출, MCP 로 tool 사용
research = await a2a_call("research-agent", query)
draft = await claude.messages.create(  # MCP tools attached
    model="claude-opus-4-7",
    tools=mcp_tools,
    messages=[{"role":"user","content": f"Draft based on: {research}"}]
)

7) Capability negotiation

card = httpx.get(agent_url + "/.well-known/agent.json").json()
if not card["capabilities"]["streaming"]:
    # 매 polling fallback
    use_polling = True

매 결정 기준

상황	Approach
매 agent ↔ tool / data	MCP
매 agent ↔ agent (cross-vendor)	A2A
매 same-process agent	Direct call (no protocol)
매 long-running (>30s)	A2A + push notification
매 strict typing 필요	A2A + JSON Schema in skill spec

기본값: 매 cross-org / cross-vendor agent collaboration 에 매 A2A, 매 internal tool wiring 은 매 MCP.

🔗 Graph

• Adjacent: OAuth 2.1

🤖 LLM 활용

언제: 매 multi-vendor agent stack 의 interop, 매 long-running specialist agent 의 호출. 언제 X: 매 single-process tool 호출 (매 MCP 를 사용), 매 latency-critical (<50ms) 의 inner loop.

❌ 안티패턴

• A2A 로 tool 호출: 매 MCP scope. 매 protocol 혼동.
• No AgentCard: 매 capability 알려주지 않으면 매 client 가 fallback 못함.
• Sync polling on long task: 매 push notification 또는 SSE 필수.
• Token leakage: 매 webhook URL 의 token 검증 누락.

🧪 검증 / 중복

• Verified (a2aproject.org spec v0.3, Linux Foundation A2A Project 2025-06-23, Anthropic A2A blog 2025).
• 신뢰도 A.

🕓 Changelog

날짜	변경
2026-05-08	Phase 1
2026-05-10	Manual cleanup — A2A protocol primitives + MCP comparison + 7 working patterns