This MCP server provides email processing capabilities for Outlook, integrating with MongoDB for semantic search and SQLite for efficient storage. It features multi-mailbox support, date range filtering, and vector embedding generation using Ollama. Designed for Windows environments, it offers tools for processing emails, storing metadata, and preparing data for advanced search and analysis tasks. The server is particularly useful for applications requiring automated email processing, semantic search capabilities, and integration with local Outlook installations.
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Process emails from a specified date range and return structured results. Input parameters include start_date (ISO format), end_date (ISO format), and mailboxes (list of mailbox names or ['All'] for all mailboxes). Outputs include success status, processed count, retrieved count, stored count, failed count, and a message.
Search for emails based on a specific query. Parameters include query (string) and optional filters like date range or mailbox.
Analyze the sentiment of a given email. Takes an email ID as input and returns sentiment analysis results.
Identify actionable items from emails. Input is typically an email ID or a list of emails, and it returns a list of identified actionable tasks.
Export email data to specified formats (CSV, JSON, HTML, Excel). Parameters include format type and optional filters like date range or mailbox.
Retrieve a list of folders in the user's Outlook account. Returns an array of folder names and their respective IDs.
Get statistics for a specific folder, including total emails, unread count, and other relevant metrics. Input is the folder ID.
Organize emails according to user-defined rules. Parameters include ruleset (definition of rules) and target mailbox or folder.
Extract contacts from specified mailboxes or folders. Returns a structured list of contacts with details.
Retrieve statistics about emails processed, including counts of processed, failed, and stored emails based on specified criteria.
Check the consistency between the SQLite database and MongoDB to ensure data integrity. Returns a report on any discrepancies found.
