OutlookメールをClaude Codeに管理させたら毎日2時間のメール処理が30分になった体験記【2026年版】

import os, json, requests
from datetime import datetime, timezone
import anthropic

TENANT_ID     = os.environ["AZURE_TENANT_ID"]
CLIENT_ID     = os.environ["AZURE_CLIENT_ID"]
CLIENT_SECRET = os.environ["AZURE_CLIENT_SECRET"]
USER_EMAIL    = os.environ["OUTLOOK_USER_EMAIL"]
GRAPH_BASE    = "https://graph.microsoft.com/v1.0"

def get_token():
    url  = f"https://login.microsoftonline.com/{TENANT_ID}/oauth2/v2.0/token"
    resp = requests.post(url, data={
        "grant_type": "client_credentials",
        "client_id": CLIENT_ID,
        "client_secret": CLIENT_SECRET,
        "scope": "https://graph.microsoft.com/.default",
    })
    return resp.json()["access_token"]

def get_unread_mails(token, top=50):
    headers = {"Authorization": f"Bearer {token}"}
    url = (
        f"{GRAPH_BASE}/users/{USER_EMAIL}/messages"
        "?$filter=isRead eq false"
        f"&$top={top}"
        "&$select=id,subject,from,receivedDateTime,bodyPreview,importance"
        "&$orderby=receivedDateTime desc"
    )
    data = requests.get(url, headers=headers).json()
    return data.get("value", [])

def generate_digest(mails):
    client = anthropic.Anthropic()
    mail_text = json.dumps([{
        "subject": m["subject"],
        "from": m["from"]["emailAddress"]["address"],
        "received": m["receivedDateTime"],
        "preview": m["bodyPreview"][:300],
    } for m in mails], ensure_ascii=False)

    resp = client.messages.create(
        model="claude-opus-4-5",
        max_tokens=2048,
        messages=[{"role": "user", "content": f"""
以下の未読Outlookメール一覧を分析し、日本語で日次ダイジェストを作成してください。

【緊急対応】【返信必要】【FYI確認】【無視可能】の4カテゴリに分類し、
各メールを「送信者 | 件名 | 一言要約」の形式でリストアップしてください。

メール一覧:
{mail_text}
"""}])
    return resp.content[0].text

if __name__ == "__main__":
    token   = get_token()
    mails   = get_unread_mails(token)
    digest  = generate_digest(mails)
    today   = datetime.now(timezone.utc).strftime("%Y-%m-%d")
    with open(f"digest_{today}.txt", "w", encoding="utf-8") as f:
        f.write(digest)
    print(f"✅ ダイジェスト生成完了: digest_{today}.txt")

import os, json, requests
import anthropic

GRAPH_BASE = "https://graph.microsoft.com/v1.0"

def get_headers(token):
    return {"Authorization": f"Bearer {token}",
            "Content-Type": "application/json"}

def ensure_folder(token, user, parent_id, name):
    """フォルダが存在しなければ作成、IDを返す"""
    if parent_id:
        url = f"{GRAPH_BASE}/users/{user}/mailFolders/{parent_id}/childFolders"
    else:
        url = f"{GRAPH_BASE}/users/{user}/mailFolders"

    # 既存フォルダを検索
    resp = requests.get(url, headers=get_headers(token)).json()
    for f in resp.get("value", []):
        if f["displayName"] == name:
            return f["id"]

    # 存在しなければ作成
    r = requests.post(url, headers=get_headers(token),
                      json={"displayName": name})
    return r.json()["id"]

def classify_mail(client, subject, sender, preview):
    """Claudeでメールのプロジェクトを判定"""
    resp = client.messages.create(
        model="claude-haiku-4-5",
        max_tokens=50,
        messages=[{"role": "user", "content":
            f"件名:{subject}\n送信者:{sender}\n本文:{preview[:200]}\n\n"
            "ProjectA/ProjectB/ProjectC/未分類 のいずれか1語で答えてください。"}]
    )
    label = resp.content[0].text.strip()
    return label if label in ["ProjectA", "ProjectB", "ProjectC"] else "未分類"

def move_mail(token, user, mail_id, dest_folder_id):
    url = f"{GRAPH_BASE}/users/{user}/messages/{mail_id}/move"
    requests.post(url, headers=get_headers(token),
                  json={"destinationId": dest_folder_id})

if __name__ == "__main__":
    from daily_digest import get_token, get_unread_mails
    import os

    user   = os.environ["OUTLOOK_USER_EMAIL"]
    token  = get_token()
    ai     = anthropic.Anthropic()

    # フォルダ構造を作成
    pid    = ensure_folder(token, user, None, "Projects")
    fmap   = {name: ensure_folder(token, user, pid, name)
               for name in ["ProjectA", "ProjectB", "ProjectC", "未分類"]}

    mails  = get_unread_mails(token, top=100)
    counts = {k: 0 for k in fmap}

    for m in mails:
        label = classify_mail(ai, m["subject"],
                               m["from"]["emailAddress"]["address"],
                               m["bodyPreview"])
        move_mail(token, user, m["id"], fmap[label])
        counts[label] += 1

    print("振り分け完了:", counts)

import os, csv, base64, requests, json
from datetime import datetime
import anthropic

GRAPH_BASE = "https://graph.microsoft.com/v1.0"

def load_recipients(csv_path):
    with open(csv_path, encoding="utf-8") as f:
        return list(csv.DictReader(f))

def personalize_body(ai_client, recipient, template):
    """Claudeで宛先ごとに本文をパーソナライズ"""
    resp = ai_client.messages.create(
        model="claude-haiku-4-5",
        max_tokens=400,
        messages=[{"role": "user", "content":
            f"以下のメールテンプレートを{recipient['company']} {recipient['name']}様向けに"
            "自然な日本語ビジネス文体でパーソナライズしてください。\n\n"
            f"テンプレート:\n{template}"}])
    return resp.content[0].text

def encode_attachment(filepath):
    with open(filepath, "rb") as f:
        return base64.b64encode(f.read()).decode()

def send_mail_with_attachment(token, user, to_email, to_name,
                                subject, body, attachment_path):
    url         = f"{GRAPH_BASE}/users/{user}/sendMail"
    filename    = os.path.basename(attachment_path)
    encoded     = encode_attachment(attachment_path)

    payload = {
        "message": {
            "subject": subject,
            "body": {"contentType": "Text", "content": body},
            "toRecipients": [{"emailAddress": {
                "address": to_email, "name": to_name
            }}],
            "attachments": [{
                "@odata.type": "#microsoft.graph.fileAttachment",
                "name": filename,
                "contentBytes": encoded,
                "contentType": "application/pdf"
            }]
        },
        "saveToSentItems": True
    }
    r = requests.post(url,
                      headers={"Authorization": f"Bearer {token}",
                               "Content-Type": "application/json"},
                      json=payload)
    return r.status_code == 202

if __name__ == "__main__":
    from daily_digest import get_token

    token      = get_token()
    user       = os.environ["OUTLOOK_USER_EMAIL"]
    ai_client  = anthropic.Anthropic()
    recipients = load_recipients("recipients.csv")
    attachment = "monthly_report_2026-04.pdf"
    subject    = "【月次レポート】2026年4月度 ご報告"
    template   = "いつも大変お世話になっております。4月度の月次レポートをお送りします。"

    print(f"送信対象: {len(recipients)} 件")
    confirm = input("本当に送信しますか？ (y/n): ")
    if confirm.lower() != "y":
        print("キャンセルしました。"); exit()

    log = []
    for r in recipients:
        body    = personalize_body(ai_client, r, template)
        success = send_mail_with_attachment(
            token, user, r["email"], r["name"], subject, body, attachment)
        log.append({"email": r["email"], "status": "OK" if success else "FAIL",
                    "sent_at": datetime.now().isoformat()})
        print(f"{'✅' if success else '❌'} {r['name']} ({r['email']})")

    with open("send_log.csv", "w", newline="", encoding="utf-8") as f:
        w = csv.DictWriter(f, fieldnames=["email", "status", "sent_at"])
        w.writeheader(); w.writerows(log)
    print("✅ 送信ログを send_log.csv に保存しました。")