Outlook MCP

""" CLI for Outlook MCP - Run indexing separately from MCP server """ import sys import argparse from datetime import datetime, timedelta def run_index(days: int = 365, clear: bool = False, batch_size: int = 50): """Run email indexing with batch processing""" print(f"Starting email indexing (last {days} days, batch size: {batch_size})...") # Import here to avoid slow startup from .outlook_reader import OutlookReader from .email_indexer import get_indexer, get_embedding_model from .config import get_config import hashlib config = get_config() print("Loading embedding model (this may take a minute)...") model = get_embedding_model() print("Model loaded!") print("Initializing indexer...") indexer = get_indexer() if clear: print("Clearing existing index...") indexer.clear_index() print("Connecting to Outlook...") reader = OutlookReader() status = reader.get_connection_status() if not status.get("connected"): print(f"Error: Could not connect to Outlook: {status.get('error')}") return print(f"Connected to: {status.get('account')}") print(f"Inbox count: {status.get('inbox_count')}") since_date = datetime.now() - timedelta(days=days) folders = ["Inbox", "Sent Items"] total_processed = 0 total_indexed = 0 total_skipped = 0 errors = [] for folder_path in folders: print(f"\nProcessing folder: {folder_path}") # Collect emails in batches email_batch = [] try: for email in reader.get_emails(folder_path=folder_path, since_date=since_date): total_processed += 1 email_batch.append(email) # Process batch when full if len(email_batch) >= batch_size: indexed, skipped, batch_errors = process_batch(indexer, model, email_batch, config) total_indexed += indexed total_skipped += skipped errors.extend(batch_errors) print(f" Processed batch: {total_indexed} indexed, {total_skipped} skipped") email_batch = [] # Process remaining emails if email_batch: indexed, skipped, batch_errors = process_batch(indexer, model, email_batch, config) total_indexed += indexed total_skipped += skipped errors.extend(batch_errors) print(f" Processed final batch: {total_indexed} indexed, {total_skipped} skipped") except Exception as e: print(f" Error accessing folder: {e}") print(f"\n=== Indexing Complete ===") print(f"Processed: {total_processed}") print(f"Indexed: {total_indexed}") print(f"Skipped: {total_skipped}") if errors: print(f"Errors: {len(errors)}") for err in errors[:5]: print(f" - {err}") def process_batch(indexer, model, emails, config): """Process a batch of emails with batch embedding""" import hashlib indexed = 0 skipped = 0 errors = [] # Prepare documents for batch encoding documents = [] valid_emails = [] for email in emails: # Generate email ID email_id = hashlib.sha256(email.entry_id.encode()).hexdigest()[:32] # Check if already indexed try: existing = indexer._emails_collection.get(ids=[email_id]) if existing and existing["ids"]: skipped += 1 continue except: pass # Prepare document parts = [] if email.subject: parts.append(f"Subject: {email.subject}") parts.append(email.subject) if email.sender_name: parts.append(f"From: {email.sender_name}") if email.recipients: parts.append(f"To: {', '.join(email.recipients[:5])}") if email.received_time: parts.append(f"Date: {email.received_time.strftime('%Y-%m-%d')}") if email.body: parts.append(email.body[:2000]) # Limit body length document = "\n".join(parts) if document: documents.append(document) valid_emails.append((email, email_id)) if not documents: return indexed, skipped, errors # Batch encode all documents try: embeddings = model.encode(documents).tolist() # Add to collection for i, (email, email_id) in enumerate(valid_emails): try: metadata = { "entry_id": email.entry_id, "subject": email.subject[:500] if email.subject else "", "sender_name": email.sender_name[:200] if email.sender_name else "", "sender_email": email.sender_email[:200] if email.sender_email else "", "folder_path": email.folder_path[:200] if email.folder_path else "", "received_time": email.received_time.isoformat() if email.received_time else "", "has_attachments": email.has_attachments, } indexer._emails_collection.add( ids=[email_id], embeddings=[embeddings[i]], documents=[documents[i][:50000]], # Limit document size (increased for Vision AI) metadatas=[metadata], ) indexed += 1 except Exception as e: errors.append(str(e)[:100]) skipped += 1 except Exception as e: errors.append(f"Batch encoding error: {str(e)[:100]}") skipped += len(valid_emails) return indexed, skipped, errors def main(): parser = argparse.ArgumentParser(description="Outlook MCP CLI") subparsers = parser.add_subparsers(dest="command") # Index command index_parser = subparsers.add_parser("index", help="Run email indexing") index_parser.add_argument("--days", type=int, default=365, help="Days to index (default: 365)") index_parser.add_argument("--clear", action="store_true", help="Clear existing index first") args = parser.parse_args() if args.command == "index": run_index(days=args.days, clear=args.clear) else: parser.print_help() if __name__ == "__main__": main()