Email Processing MCP Server

This MCP server provides email processing capabilities with MongoDB integration for semantic search and SQLite for efficient storage and retrieval.

Features

Process emails from Outlook with date range filtering
Store emails in SQLite database with proper connection management
Generate vector embeddings using Ollama
Multi-mailbox support
Support for Inbox, Sent Items, and optionally Deleted Items folders

Upcoming Features

Email search with semantic capabilities
Email summarization using LLMs
Automatic email categorization
Customizable email reports
Advanced filtering options
Outlook drafting email responses
Outlook rule suggestions
Expanded database options with Neo4j and ChromaDB integration

Prerequisites

Python 3.10 or higher
Ollama running locally (for embeddings)
Microsoft Outlook installed
Windows OS (for Outlook integration)
MongoDB server (for storing embeddings)

Installation

Install uv (if not already installed):

pip install uv

Create a virtual environment:

uv venv .venv

Activate the virtual environment:

Windows:
```
.venv\Scripts\activate
```
macOS/Linux:
```
source .venv/bin/activate
```
Install dependencies:

uv pip install -e .

Install the fastmcp package:

uv pip install fastmcp

Make sure Ollama is running locally with required models:

ollama pull nomic-embed-text

Configuration

Add the server to your Claude for Desktop configuration file:

Windows: %APPDATA%\Claude\claude_desktop_config.json
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "outlook-email": {
      "command": "C:/Users/username/path/to/mcp-server-outlook-email/.venv/Scripts/python",
      "args": [
        "C:/Users/username/path/to/mcp-server-outlook-email/src/mcp_server.py"
      ],
      "env": {
        "MONGODB_URI": "mongodb://localhost:27017/MCP?authSource=admin",
        "SQLITE_DB_PATH": "C:\\Users\\username\\path\\to\\mcp-server-outlook-email\\data\\emails.db",
        "EMBEDDING_BASE_URL": "http://localhost:11434",
        "EMBEDDING_MODEL": "nomic-embed-text",
        "COLLECTION_NAME": "outlook-emails",
        "PROCESS_DELETED_ITEMS": "false"
      }
    }
  }
}

Tracing and Monitoring

The server has been designed to support external tracing and monitoring solutions. The MCP logging implementation has been intentionally removed in favor of a more robust tracing approach that will be implemented separately.

Note: Do not attempt to re-implement the previous logging system. A new tracing solution will be provided in the future.

Configuration fields explained:

command: Full path to the Python executable in your virtual environment
args: Array containing the full path to the MCP server script
env: Environment variables for configuration
- MONGODB_URI: MongoDB connection string
- SQLITE_DB_PATH: Absolute path to SQLite database file
- EMBEDDING_BASE_URL: Ollama server URL
- EMBEDDING_MODEL: Model to use for embeddings
- LLM_MODEL: Model to use for LLM operations
- COLLECTION_NAME: Name of the MongoDB collection to use (required)
- PROCESS_DELETED_ITEMS: Whether to process emails from the Deleted Items folder (optional, default: "false")
disabled: Whether the server is disabled (should be false)
alwaysAllow: Array of tools that don't require user confirmation
autoApprove: Array of tools that can be auto-approved

Replace the paths with the actual paths on your system. Note that Windows paths in the env section should use double backslashes.

Available Tools

1. process_emails

Process emails from a specified date range:

{
  "start_date": "2024-01-01",    # ISO format date (YYYY-MM-DD)
  "end_date": "2024-02-15",      # ISO format date (YYYY-MM-DD)
  "mailboxes": ["All"]           # List of mailbox names or ["All"] for all mailboxes
}

The tool will:

Connect to specified Outlook mailboxes
Retrieve emails from Inbox and Sent Items folders (and Deleted Items if enabled)
Store emails in SQLite database
Generate embeddings using Ollama
Store embeddings in MongoDB for semantic search

Example Usage in Claude

"Process emails from February 1st to February 17th from all mailboxes"

Architecture

The server uses a hybrid search approach:

SQLite database for:
- Primary email storage
- Full-text search capabilities
- Processing status tracking
- Efficient filtering
- Directory is created automatically if it doesn't exist
- Connections are properly closed to prevent database locking
MongoDB for:
- Vector embeddings storage
- Semantic similarity search
- Metadata filtering
- Efficient retrieval
- Connections are properly closed after use

Error Handling

The server provides detailed error messages for common issues:

Invalid date formats
Connection issues with Outlook
MongoDB errors
Embedding generation failures with retry logic
SQLite storage errors
Ollama server connection issues with automatic retries

Resource Management

The server implements proper resource management to prevent issues:

Database connections (SQLite and MongoDB) are kept open during the server's lifetime to prevent "Cannot operate on a closed database" errors
Connections are only closed when the server shuts down, using an atexit handler
Destructors and context managers are used as a fallback to ensure connections are closed when objects are garbage collected
Connection management is designed to balance resource usage with operational reliability
Robust retry logic for external services like Ollama to handle temporary connection issues

Security Notes

The server only processes emails from specified mailboxes
All data is stored locally (SQLite) and in MongoDB
No external API calls except to local Ollama server
Requires explicit user approval for email processing
No sensitive email data is exposed through the MCP interface

Debugging

If you encounter issues:

Verify emails were successfully processed (check process_emails response)
Ensure Ollama server is running for embedding generation
Check that the SQLite database is accessible
Verify MongoDB connection is working properly