MCPサーバーでExcel生成時のデータ改変を防ぐ ― AgentCore/LLMをデータ経路から外す設計

mcp-server/
├── main.py                   # FastMCPエントリーポイント
├── core/
│   ├── db.py                 # Oracleコネクションプール管理
│   ├── runner.py             # テンプレート実行のコアロジック
│   ├── excel_writer.py       # openpyxlでのExcel読み書き
│   ├── hash_verify.py        # SHA-256によるカラム単位の整合性検証
│   └── s3_publisher.py       # S3アップロード & Presigned URL発行
├── tools/                    # MCPツール定義
│   ├── product_list.py       # 商品一覧Excel生成ツール
│   ├── sales_summary.py      # 売上サマリExcel生成ツール
│   └── low_stock.py          # 在庫不足Excel生成ツール
├── sql_templates/            # パラメータ付きSQLテンプレート
│   ├── product_list.sql
│   ├── sales_summary.sql
│   └── low_stock.sql
└── column_mappings/          # SQLカラム → Excelカラムの対応定義
    ├── product_list.yaml
    ├── sales_summary.yaml
    └── low_stock.yaml

-- sql_templates/product_list.sql
SELECT
  PRODUCT_ID, PRODUCT_NAME, CATEGORY, UNIT_PRICE, STOCK_QTY, REGISTERED_AT
FROM verify_owner.PRODUCTS
WHERE 1 = 1
  AND (:category IS NULL OR CATEGORY = :category)
  AND (:min_price IS NULL OR UNIT_PRICE >= :min_price)
  AND (:max_price IS NULL OR UNIT_PRICE <= :max_price)
  AND (:name_pattern IS NULL OR PRODUCT_NAME LIKE '%' || :name_pattern || '%')
ORDER BY PRODUCT_ID

# column_mappings/product_list.yaml
template_key: templates/product_list_template.xlsx
sheet_name: ProductList
start_row: 2
column_to_excel_col:
  PRODUCT_ID: 1      # → Excel A列
  PRODUCT_NAME: 2    # → Excel B列
  CATEGORY: 3        # → Excel C列
  UNIT_PRICE: 4      # → Excel D列
  STOCK_QTY: 5       # → Excel E列
  REGISTERED_AT: 6   # → Excel F列

# tools/product_list.py
def register(mcp: FastMCP) -> None:
    @mcp.tool()
    def create_product_list_excel(
        category: str | None = None,
        min_price: float | None = None,
        max_price: float | None = None,
        name_pattern: str | None = None,
    ) -> dict[str, Any]:
        """商品一覧のExcelファイルを生成する"""
        params: dict[str, Any] = {
            "category": category,
            "min_price": min_price,
            "max_price": max_price,
            "name_pattern": name_pattern,
        }
        return execute_template_tool("product_list", params)

# core/hash_verify.py
def hash_column(values: list[Any]) -> str:
    hasher = hashlib.sha256()
    for v in values:
        if v is None:
            hasher.update(b"\x00<NULL>\x00")
        elif isinstance(v, (int, float, Decimal)):
            hasher.update(b"\x04")
            hasher.update(repr(float(v)).encode("utf-8"))
        elif isinstance(v, datetime):
            hasher.update(b"\x02")
            hasher.update(v.isoformat().encode("utf-8"))
        elif isinstance(v, date):
            hasher.update(b"\x03")
            hasher.update(v.isoformat().encode("utf-8"))
        else:
            hasher.update(b"\x05")
            hasher.update(str(v).encode("utf-8"))
        hasher.update(b"\x00")
    return hasher.hexdigest()

# core/runner.py（抜粋）

# --- SQL実行後 ---
sql_hashes = hash_verify.hash_rows_per_column(rows, columns)

# --- Excel書き込み → 読み戻し後 ---
excel_rows = excel_writer.read_back_columns(
    workbook, sheet_name, start_row, len(rows), columns, column_to_excel_col,
)
excel_hashes = hash_verify.hash_rows_per_column(excel_rows, columns)

# --- 検証 ---
if sql_hashes != excel_hashes:
    raise IntegrityError(
        f"Hash mismatch between SQL result and Excel content for template {template_id}"
    )

SELECT PRODUCT_ID, PRODUCT_NAME, CATEGORY, STOCK_QTY, UNIT_PRICE
FROM verify_owner.PRODUCTS
WHERE STOCK_QTY < 20
  AND (NULL IS NULL OR CATEGORY = NULL)
ORDER BY STOCK_QTY ASC, PRODUCT_ID

PRODUCT_ID | PRODUCT_NAME | CATEGORY   | STOCK_QTY | UNIT_PRICE
-----------+--------------+------------+-----------+-----------
1          | Widget-A-01  | Category-1 | 0         | 100.0
30         | Widget-J-03  | Category-5 | 1         | 4073.0
59         | Widget-I-06  | Category-4 | 2         | 8046.0
88         | Widget-H-09  | Category-3 | 3         | 2119.0
16         | Widget-F-02  | Category-1 | 4         | 2155.0
45         | Widget-E-05  | Category-5 | 5         | 6128.0
74         | Widget-D-08  | Category-4 | 6         | 201.0
2          | Widget-B-01  | Category-2 | 7         | 237.0
31         | Widget-A-04  | Category-1 | 8         | 4210.0
60         | Widget-J-06  | Category-5 | 9         | 8183.0
89         | Widget-I-09  | Category-4 | 10        | 2256.0
17         | Widget-G-02  | Category-2 | 11        | 2292.0
46         | Widget-F-05  | Category-1 | 12        | 6265.0
75         | Widget-E-08  | Category-5 | 13        | 338.0
3          | Widget-C-01  | Category-3 | 14        | 374.0
32         | Widget-B-04  | Category-2 | 15        | 4347.0
61         | Widget-A-07  | Category-1 | 16        | 8320.0
90         | Widget-J-09  | Category-5 | 17        | 2393.0
18         | Widget-H-02  | Category-3 | 18        | 2429.0
47         | Widget-G-05  | Category-2 | 19        | 6402.0