diff --git a/mess_log_processing/src/mess_log_processing/cli.py b/mess_log_processing/src/mess_log_processing/cli.py
new file mode 100644
index 0000000..02931ee
--- /dev/null
+++ b/mess_log_processing/src/mess_log_processing/cli.py
@@ -0,0 +1,80 @@
+import argparse
+import logging
+import sys
+from pathlib import Path
+
+import pandas as pd
+
+from mess_log_processing.core import process_logs
+
+
+def _configure_logging(level: int = logging.INFO) -> None:
+    """Configure simple logging for CLI execution."""
+    logging.basicConfig(
+        level=level,
+        format="%(asctime)s [%(levelname)s] %(message)s",
+        datefmt="%Y-%m-%d %H:%M:%S",
+    )
+
+
+def main(argv: list[str] | None = None) -> None:
+    """Command-line interface for processing measurement logs.
+
+    Uses argparse to receive JSON and CSV input file paths and an optional output path.
+    """
+    parser = argparse.ArgumentParser(
+        description="Analyse und Aggregation von Messdaten (pinned/unpinned) mit p99-Statistiken."
+    )
+    parser.add_argument(
+        "--json",
+        required=True,
+        help="Pfad zur Eingabe-JSONL-Datei mit Messdaten.",
+    )
+    parser.add_argument(
+        "--csv",
+        required=True,
+        help="Pfad zur Eingabe-CSV-Datei mit Messdaten.",
+    )
+    parser.add_argument(
+        "--out",
+        required=False,
+        help="Pfad zur Ausgabedatei für aggregierte Statistik (CSV).",
+    )
+
+    args = parser.parse_args(argv)
+
+    _configure_logging()
+    logger = logging.getLogger(__name__)
+
+    json_path = Path(args.json)
+    csv_path = Path(args.csv)
+    output_path = Path(args.out) if args.out else None
+
+    # Validate input paths
+    if not json_path.exists() or not json_path.is_file():
+        logger.error("JSON input file not found or invalid: %s", json_path)
+        sys.exit(1)
+    if not csv_path.exists() or not csv_path.is_file():
+        logger.error("CSV input file not found or invalid: %s", csv_path)
+        sys.exit(1)
+
+    try:
+        logger.info("Processing logs: %s and %s", json_path, csv_path)
+        result_df: pd.DataFrame = process_logs(str(json_path), str(csv_path))
+        logger.info("Processing complete. %d records aggregated.", len(result_df))
+    except Exception as exc:  # noqa: BLE001
+        logger.exception("Error during log processing: %s", exc)
+        sys.exit(1)
+
+    if output_path:
+        try:
+            output_path.parent.mkdir(parents=True, exist_ok=True)
+            result_df.to_csv(output_path, index=False)
+            logger.info("Statistics saved to: %s", output_path)
+        except Exception as exc:  # noqa: BLE001
+            logger.exception("Failed to write output CSV: %s", exc)
+            sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()