Gmail-MCP-Server

A Model Context Protocol (MCP) server for Gmail integration in Claude Desktop with auto authentication support. This server enables AI assistants to manage Gmail through natural language interactions.

Stars: 126

Visit

Gmail AutoAuth MCP Server is a Model Context Protocol (MCP) server designed for Gmail integration in Claude Desktop. It supports auto authentication and enables AI assistants to manage Gmail through natural language interactions. The server provides comprehensive features for sending emails, reading messages, managing labels, searching emails, and batch operations. It offers full support for international characters, email attachments, and Gmail API integration. Users can install and authenticate the server via Smithery or manually with Google Cloud Project credentials. The server supports both Desktop and Web application credentials, with global credential storage for convenience. It also includes Docker support and instructions for cloud server authentication.

README:

Gmail AutoAuth MCP Server

Features

Send emails with subject, content, attachments, and recipients
Full support for international characters in subject lines and email content
Read email messages by ID with advanced MIME structure handling
View email attachments information (filenames, types, sizes)
Search emails with various criteria (subject, sender, date range)
Comprehensive label management with ability to create, update, delete and list labels
List all available Gmail labels (system and user-defined)
List emails in inbox, sent, or custom labels
Mark emails as read/unread
Move emails to different labels/folders
Delete emails
Batch operations for efficiently processing multiple emails at once
Full integration with Gmail API
Simple OAuth2 authentication flow with auto browser launch
Support for both Desktop and Web application credentials
Global credential storage for convenience

Installation & Authentication

Installing via Smithery

To install Gmail AutoAuth for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @gongrzhe/server-gmail-autoauth-mcp --client claude

Installing Manually

Create a Google Cloud Project and obtain credentials:

a. Create a Google Cloud Project:
- Go to Google Cloud Console
- Create a new project or select an existing one
- Enable the Gmail API for your project
b. Create OAuth 2.0 Credentials:
- Go to "APIs & Services" > "Credentials"
- Click "Create Credentials" > "OAuth client ID"
- Choose either "Desktop app" or "Web application" as application type
- Give it a name and click "Create"
- For Web application, add http://localhost:3000/oauth2callback to the authorized redirect URIs
- Download the JSON file of your client's OAuth keys
- Rename the key file to gcp-oauth.keys.json
Run Authentication:

You can authenticate in two ways:

a. Global Authentication (Recommended):
```
# First time: Place gcp-oauth.keys.json in your home directory's .gmail-mcp folder
mkdir -p ~/.gmail-mcp
mv gcp-oauth.keys.json ~/.gmail-mcp/

# Run authentication from anywhere
npx @gongrzhe/server-gmail-autoauth-mcp auth
```
b. Local Authentication:
```
# Place gcp-oauth.keys.json in your current directory
# The file will be automatically copied to global config
npx @gongrzhe/server-gmail-autoauth-mcp auth
```
The authentication process will:
- Look for gcp-oauth.keys.json in the current directory or ~/.gmail-mcp/
- If found in current directory, copy it to ~/.gmail-mcp/
- Open your default browser for Google authentication
- Save credentials as ~/.gmail-mcp/credentials.json
Note:
- After successful authentication, credentials are stored globally in ~/.gmail-mcp/ and can be used from any directory
- Both Desktop app and Web application credentials are supported
- For Web application credentials, make sure to add http://localhost:3000/oauth2callback to your authorized redirect URIs
Configure in Claude Desktop:

{
  "mcpServers": {
    "gmail": {
      "command": "npx",
      "args": [
        "@gongrzhe/server-gmail-autoauth-mcp"
      ]
    }
  }
}

Docker Support

If you prefer using Docker:

Authentication:

docker run -i --rm \
  --mount type=bind,source=/path/to/gcp-oauth.keys.json,target=/gcp-oauth.keys.json \
  -v mcp-gmail:/gmail-server \
  -e GMAIL_OAUTH_PATH=/gcp-oauth.keys.json \
  -e "GMAIL_CREDENTIALS_PATH=/gmail-server/credentials.json" \
  -p 3000:3000 \
  mcp/gmail auth

Usage:

{
  "mcpServers": {
    "gmail": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-v",
        "mcp-gmail:/gmail-server",
        "-e",
        "GMAIL_CREDENTIALS_PATH=/gmail-server/credentials.json",
        "mcp/gmail"
      ]
    }
  }
}

Cloud Server Authentication

For cloud server environments (like n8n), you can specify a custom callback URL during authentication:

npx @gongrzhe/server-gmail-autoauth-mcp auth https://gmail.gongrzhe.com/oauth2callback

Setup Instructions for Cloud Environment

Configure Reverse Proxy:
- Set up your n8n container to expose a port for authentication
- Configure a reverse proxy to forward traffic from your domain (e.g., gmail.gongrzhe.com) to this port
DNS Configuration:
- Add an A record in your DNS settings to resolve your domain to your cloud server's IP address
Google Cloud Platform Setup:
- In your Google Cloud Console, add your custom domain callback URL (e.g., https://gmail.gongrzhe.com/oauth2callback) to the authorized redirect URIs list

Run Authentication:

npx @gongrzhe/server-gmail-autoauth-mcp auth https://gmail.gongrzhe.com/oauth2callback

Configure in your application:

{
  "mcpServers": {
    "gmail": {
      "command": "npx",
      "args": [
        "@gongrzhe/server-gmail-autoauth-mcp"
      ]
    }
  }
}

This approach allows authentication flows to work properly in environments where localhost isn't accessible, such as containerized applications or cloud servers.

Available Tools

The server provides the following tools that can be used through Claude Desktop:

1. Send Email (`send_email`)

Sends a new email immediately.

{
  "to": ["[email protected]"],
  "subject": "Meeting Tomorrow",
  "body": "Hi,\n\nJust a reminder about our meeting tomorrow at 10 AM.\n\nBest regards",
  "cc": ["[email protected]"],
  "bcc": ["[email protected]"]
}

2. Draft Email (`draft_email`)

Creates a draft email without sending it.

{
  "to": ["[email protected]"],
  "subject": "Draft Report",
  "body": "Here's the draft report for your review.",
  "cc": ["[email protected]"]
}

3. Read Email (`read_email`)

Retrieves the content of a specific email by its ID.

{
  "messageId": "182ab45cd67ef"
}

4. Search Emails (`search_emails`)

Searches for emails using Gmail search syntax.

{
  "query": "from:[email protected] after:2024/01/01 has:attachment",
  "maxResults": 10
}

5. Modify Email (`modify_email`)

Adds or removes labels from emails (move to different folders, archive, etc.).

{
  "messageId": "182ab45cd67ef",
  "addLabelIds": ["IMPORTANT"],
  "removeLabelIds": ["INBOX"]
}

6. Delete Email (`delete_email`)

Permanently deletes an email.

{
  "messageId": "182ab45cd67ef"
}

7. List Email Labels (`list_email_labels`)

Retrieves all available Gmail labels.

{}

8. Create Label (`create_label`)

Creates a new Gmail label.

{
  "name": "Important Projects",
  "messageListVisibility": "show",
  "labelListVisibility": "labelShow"
}

9. Update Label (`update_label`)

Updates an existing Gmail label.

{
  "id": "Label_1234567890",
  "name": "Urgent Projects",
  "messageListVisibility": "show",
  "labelListVisibility": "labelShow"
}

10. Delete Label (`delete_label`)

Deletes a Gmail label.

{
  "id": "Label_1234567890"
}

11. Get or Create Label (`get_or_create_label`)

Gets an existing label by name or creates it if it doesn't exist.

{
  "name": "Project XYZ",
  "messageListVisibility": "show",
  "labelListVisibility": "labelShow"
}

12. Batch Modify Emails (`batch_modify_emails`)

Modifies labels for multiple emails in efficient batches.

{
  "messageIds": ["182ab45cd67ef", "182ab45cd67eg", "182ab45cd67eh"],
  "addLabelIds": ["IMPORTANT"],
  "removeLabelIds": ["INBOX"],
  "batchSize": 50
}

13. Batch Delete Emails (`batch_delete_emails`)

Permanently deletes multiple emails in efficient batches.

{
  "messageIds": ["182ab45cd67ef", "182ab45cd67eg", "182ab45cd67eh"],
  "batchSize": 50
}

Advanced Search Syntax

The search_emails tool supports Gmail's powerful search operators:

Operator	Example	Description
`from:`	`from:[email protected]`	Emails from a specific sender
`to:`	`to:[email protected]`	Emails sent to a specific recipient
`subject:`	`subject:"meeting notes"`	Emails with specific text in the subject
`has:attachment`	`has:attachment`	Emails with attachments
`after:`	`after:2024/01/01`	Emails received after a date
`before:`	`before:2024/02/01`	Emails received before a date
`is:`	`is:unread`	Emails with a specific state
`label:`	`label:work`	Emails with a specific label

You can combine multiple operators: from:[email protected] after:2024/01/01 has:attachment

Advanced Features

Email Content Extraction

The server intelligently extracts email content from complex MIME structures:

Prioritizes plain text content when available
Falls back to HTML content if plain text is not available
Handles multi-part MIME messages with nested parts
Processes attachments information (filename, type, size)
Preserves original email headers (From, To, Subject, Date)

International Character Support

The server fully supports non-ASCII characters in email subjects and content, including:

Turkish, Chinese, Japanese, Korean, and other non-Latin alphabets
Special characters and symbols
Proper encoding ensures correct display in email clients

Comprehensive Label Management

The server provides a complete set of tools for managing Gmail labels:

Create Labels: Create new labels with customizable visibility settings
Update Labels: Rename labels or change their visibility settings
Delete Labels: Remove user-created labels (system labels are protected)
Find or Create: Get a label by name or automatically create it if not found
List All Labels: View all system and user labels with detailed information
Label Visibility Options: Control how labels appear in message and label lists

Label visibility settings include:

messageListVisibility: Controls whether the label appears in the message list (show or hide)
labelListVisibility: Controls how the label appears in the label list (labelShow, labelShowIfUnread, or labelHide)

These label management features enable sophisticated organization of emails directly through Claude, without needing to switch to the Gmail interface.

Batch Operations

The server includes efficient batch processing capabilities:

Process up to 50 emails at once (configurable batch size)
Automatic chunking of large email sets to avoid API limits
Detailed success/failure reporting for each operation
Graceful error handling with individual retries
Perfect for bulk inbox management and organization tasks

Security Notes

OAuth credentials are stored securely in your local environment (~/.gmail-mcp/)
The server uses offline access to maintain persistent authentication
Never share or commit your credentials to version control
Regularly review and revoke unused access in your Google Account settings
Credentials are stored globally but are only accessible by the current user

Troubleshooting

OAuth Keys Not Found
- Make sure gcp-oauth.keys.json is in either your current directory or ~/.gmail-mcp/
- Check file permissions
Invalid Credentials Format
- Ensure your OAuth keys file contains either web or installed credentials
- For web applications, verify the redirect URI is correctly configured
Port Already in Use
- If port 3000 is already in use, please free it up before running authentication
- You can find and stop the process using that port
Batch Operation Failures
- If batch operations fail, they automatically retry individual items
- Check the detailed error messages for specific failures
- Consider reducing the batch size if you encounter rate limiting

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT

Support

If you encounter any issues or have questions, please file an issue on the GitHub repository.

For Tasks:

Click tags to check more tools for each tasks

send email read email search emails modify email labels delete email

For Jobs:

ai assistant developer email marketing specialist software engineer data analyst virtual assistant

Alternative AI tools for Gmail-MCP-Server

Similar Open Source Tools

Gmail-MCP-Server

github

: 126

context7

Context7 is a powerful tool for analyzing and visualizing data in various formats. It provides a user-friendly interface for exploring datasets, generating insights, and creating interactive visualizations. With advanced features such as data filtering, aggregation, and customization, Context7 is suitable for both beginners and experienced data analysts. The tool supports a wide range of data sources and formats, making it versatile for different use cases. Whether you are working on exploratory data analysis, data visualization, or data storytelling, Context7 can help you uncover valuable insights and communicate your findings effectively.

github

: 46.3k

trapster-community

Trapster Community is a low-interaction honeypot designed for internal networks or credential capture. It monitors and detects suspicious activities, providing deceptive security layer. Features include mimicking network services, asynchronous framework, easy configuration, expandable services, and HTTP honeypot engine with AI capabilities. Supported protocols include DNS, HTTP/HTTPS, FTP, LDAP, MSSQL, POSTGRES, RDP, SNMP, SSH, TELNET, VNC, and RSYNC. The tool generates various types of logs and offers HTTP engine with AI capabilities to emulate websites using YAML configuration. Contributions are welcome under AGPLv3+ license.

github

: 141

mcpdoc

The MCP LLMS-TXT Documentation Server is an open-source server that provides developers full control over tools used by applications like Cursor, Windsurf, and Claude Code/Desktop. It allows users to create a user-defined list of `llms.txt` files and use a `fetch_docs` tool to read URLs within these files, enabling auditing of tool calls and context returned. The server supports various applications and provides a way to connect to them, configure rules, and test tool calls for tasks related to documentation retrieval and processing.

github

: 148

shortest

Shortest is an AI-powered natural language end-to-end testing framework built on Playwright. It provides a seamless testing experience by allowing users to write tests in natural language and execute them using Anthropic Claude API. The framework also offers GitHub integration with 2FA support, making it suitable for testing web applications with complex authentication flows. Shortest simplifies the testing process by enabling users to run tests locally or in CI/CD pipelines, ensuring the reliability and efficiency of web applications.

github

: 4.4k

ai-gateway

LangDB AI Gateway is an open-source enterprise AI gateway built in Rust. It provides a unified interface to all LLMs using the OpenAI API format, focusing on high performance, enterprise readiness, and data control. The gateway offers features like comprehensive usage analytics, cost tracking, rate limiting, data ownership, and detailed logging. It supports various LLM providers and provides OpenAI-compatible endpoints for chat completions, model listing, embeddings generation, and image generation. Users can configure advanced settings, such as rate limiting, cost control, dynamic model routing, and observability with OpenTelemetry tracing. The gateway can be run with Docker Compose and integrated with MCP tools for server communication.

github

: 675

mcphub.nvim

MCPHub.nvim is a powerful Neovim plugin that integrates MCP (Model Context Protocol) servers into your workflow. It offers a centralized config file for managing servers and tools, with an intuitive UI for testing resources. Ideal for LLM integration, it provides programmatic API access and interactive testing through the `:MCPHub` command.

github

: 448

clewdr

Clewdr is a collaborative platform for data analysis and visualization. It allows users to upload datasets, perform various data analysis tasks, and create interactive visualizations. The platform supports multiple users working on the same project simultaneously, enabling real-time collaboration and sharing of insights. Clewdr is designed to streamline the data analysis process and facilitate communication among team members. With its user-friendly interface and powerful features, Clewdr is suitable for data scientists, analysts, researchers, and anyone working with data to gain valuable insights and make informed decisions.

github

: 938

mcp-redis

The Redis MCP Server is a natural language interface designed for agentic applications to efficiently manage and search data in Redis. It integrates seamlessly with MCP (Model Content Protocol) clients, enabling AI-driven workflows to interact with structured and unstructured data in Redis. The server supports natural language queries, seamless MCP integration, full Redis support for various data types, search and filtering capabilities, scalability, and lightweight design. It provides tools for managing data stored in Redis, such as string, hash, list, set, sorted set, pub/sub, streams, JSON, query engine, and server management. Installation can be done from PyPI or GitHub, with options for testing, development, and Docker deployment. Configuration can be via command line arguments or environment variables. Integrations include OpenAI Agents SDK, Augment, Claude Desktop, and VS Code with GitHub Copilot. Use cases include AI assistants, chatbots, data search & analytics, and event processing. Contributions are welcome under the MIT License.

github

: 236

llm-web-api

LLM Web API is a tool that provides a web page to API interface for ChatGPT, allowing users to bypass Cloudflare challenges, switch models, and dynamically display supported models. It uses Playwright to control a fingerprint browser, simulating user operations to send requests to the OpenAI website and converting the responses into API interfaces. The API currently supports the OpenAI-compatible /v1/chat/completions API, accessible using OpenAI or other compatible clients.

github

: 68

scylla

Scylla is an intelligent proxy pool tool designed for humanities, enabling users to extract content from the internet and build their own Large Language Models in the AI era. It features automatic proxy IP crawling and validation, an easy-to-use JSON API, a simple web-based user interface, HTTP forward proxy server, Scrapy and requests integration, and headless browser crawling. Users can start using Scylla with just one command, making it a versatile tool for various web scraping and content extraction tasks.

github

: 3.9k

claim-ai-phone-bot

AI-powered call center solution with Azure and OpenAI GPT. The bot can answer calls, understand the customer's request, and provide relevant information or assistance. It can also create a todo list of tasks to complete the claim, and send a report after the call. The bot is customizable, and can be used in multiple languages.

github

: 65

perplexity-mcp

Perplexity-mcp is a Model Context Protocol (MCP) server that provides web search functionality using Perplexity AI's API. It works with the Anthropic Claude desktop client. The server allows users to search the web with specific queries and filter results by recency. It implements the perplexity_search_web tool, which takes a query as a required argument and can filter results by day, week, month, or year. Users need to set up environment variables, including the PERPLEXITY_API_KEY, to use the server. The tool can be installed via Smithery and requires UV for installation. It offers various models for different contexts and can be added as an MCP server in Cursor or Claude Desktop configurations.

github

: 70

snak

The starknet-agent-kit is a toolkit designed for creating AI agents that can interact with the Starknet blockchain. It provides support for multiple AI providers such as Anthropic, OpenAI, Google Gemini, and Ollama. The kit includes an NPM package and a NestJS server with a web interface. Users can run the server in different modes like Chat Mode for conversations, checking balances, executing transfers, and managing accounts, as well as Autonomous Mode for automated monitoring. Additionally, the kit offers a library mode for more advanced usage, allowing users to interact with the StarknetAgent class for executing specific actions. The kit aims to simplify the process of integrating AI capabilities with blockchain interactions.

github

: 82

claude-task-master

Claude Task Master is a task management system designed for AI-driven development with Claude, seamlessly integrating with Cursor AI. It allows users to configure tasks through environment variables, parse PRD documents, generate structured tasks with dependencies and priorities, and manage task status. The tool supports task expansion, complexity analysis, and smart task recommendations. Users can interact with the system through CLI commands for task discovery, implementation, verification, and completion. It offers features like task breakdown, dependency management, and AI-driven task generation, providing a structured workflow for efficient development.

github

: 22.3k

mcp-victoriametrics

The VictoriaMetrics MCP Server is an implementation of Model Context Protocol (MCP) server for VictoriaMetrics. It provides access to your VictoriaMetrics instance and seamless integration with VictoriaMetrics APIs and documentation. The server allows you to use almost all read-only APIs of VictoriaMetrics, enabling monitoring, observability, and debugging tasks related to your VictoriaMetrics instances. It also contains embedded up-to-date documentation and tools for exploring metrics, labels, alerts, and more. The server can be used for advanced automation and interaction capabilities for engineers and tools.

github

: 70

For similar tasks

Gmail-MCP-Server

github

: 126

UFO

UFO is a UI-focused dual-agent framework to fulfill user requests on Windows OS by seamlessly navigating and operating within individual or spanning multiple applications.

github

: 6.6k

For similar jobs

zep

Zep is a long-term memory service for AI Assistant apps. With Zep, you can provide AI assistants with the ability to recall past conversations, no matter how distant, while also reducing hallucinations, latency, and cost. Zep persists and recalls chat histories, and automatically generates summaries and other artifacts from these chat histories. It also embeds messages and summaries, enabling you to search Zep for relevant context from past conversations. Zep does all of this asyncronously, ensuring these operations don't impact your user's chat experience. Data is persisted to database, allowing you to scale out when growth demands. Zep also provides a simple, easy to use abstraction for document vector search called Document Collections. This is designed to complement Zep's core memory features, but is not designed to be a general purpose vector database. Zep allows you to be more intentional about constructing your prompt: 1. automatically adding a few recent messages, with the number customized for your app; 2. a summary of recent conversations prior to the messages above; 3. and/or contextually relevant summaries or messages surfaced from the entire chat session. 4. and/or relevant Business data from Zep Document Collections.

github

: 2.4k

doc2plan

doc2plan is a browser-based application that helps users create personalized learning plans by extracting content from documents. It features a Creator for manual or AI-assisted plan construction and a Viewer for interactive plan navigation. Users can extract chapters, key topics, generate quizzes, and track progress. The application includes AI-driven content extraction, quiz generation, progress tracking, plan import/export, assistant management, customizable settings, viewer chat with text-to-speech and speech-to-text support, and integration with various Retrieval-Augmented Generation (RAG) models. It aims to simplify the creation of comprehensive learning modules tailored to individual needs.

github

: 138

whatsapp-chatgpt

This repository contains a WhatsApp bot that utilizes OpenAI's GPT and DALL-E 2 to respond to user inputs. Users can interact with the bot through voice messages, which are transcribed and responded to. The bot requires Node.js, npm, an OpenAI API key, and a WhatsApp account. It uses Puppeteer to run a real instance of Whatsapp Web to avoid being blocked. However, there is a risk of being blocked by WhatsApp as it does not allow bots or unofficial clients on its platform. The bot is not free to use, and users will be charged by OpenAI for each request made.

github

: 3.4k

OmniSteward

OmniSteward is an AI-powered steward system based on large language models that can interact with users through voice or text to help control smart home devices and computer programs. It supports multi-turn dialogue, tool calling for complex tasks, multiple LLM models, voice recognition, smart home control, computer program management, online information retrieval, command line operations, and file management. The system is highly extensible, allowing users to customize and share their own tools.

github

: 66

chatgpt-wechat

ChatGPT-WeChat is a personal assistant application that can be safely used on WeChat through enterprise WeChat without the risk of being banned. The project is open source and free, with no paid sections or external traffic operations except for advertising on the author's public account '积木成楼'. It supports various features such as secure usage on WeChat, multi-channel customer service message integration, proxy support, session management, rapid message response, voice and image messaging, drawing capabilities, private data storage, plugin support, and more. Users can also develop their own capabilities following the rules provided. The project is currently in development with stable versions available for use.

github

: 996

mcp-agent

mcp-agent is a simple, composable framework designed to build agents using the Model Context Protocol. It handles the lifecycle of MCP server connections and implements patterns for building production-ready AI agents in a composable way. The framework also includes OpenAI's Swarm pattern for multi-agent orchestration in a model-agnostic manner, making it the simplest way to build robust agent applications. It is purpose-built for the shared protocol MCP, lightweight, and closer to an agent pattern library than a framework. mcp-agent allows developers to focus on the core business logic of their AI applications by handling mechanics such as server connections, working with LLMs, and supporting external signals like human input.

github

: 7.4k

Gmail-MCP-Server

github

: 126

Operit

Operit AI is a fully functional AI assistant application for mobile devices, running independently on Android devices with powerful tool invocation capabilities. It offers over 40 built-in tools for file system operations, HTTP requests, system operations, UI automation, and media processing. The app combines these tools with rich plugins to enable a wide range of tasks, from simple to complex, providing a comprehensive experience of a smartphone AI assistant.

github

: 3.3k

Gmail-MCP-Server

README:

Gmail AutoAuth MCP Server

Features

Installation & Authentication

Installing via Smithery

Installing Manually

Docker Support

Cloud Server Authentication

Setup Instructions for Cloud Environment

Available Tools

1. Send Email (send_email)

2. Draft Email (draft_email)

3. Read Email (read_email)

4. Search Emails (search_emails)

5. Modify Email (modify_email)

6. Delete Email (delete_email)

7. List Email Labels (list_email_labels)

8. Create Label (create_label)

9. Update Label (update_label)

10. Delete Label (delete_label)

11. Get or Create Label (get_or_create_label)

12. Batch Modify Emails (batch_modify_emails)

13. Batch Delete Emails (batch_delete_emails)

Advanced Search Syntax

Advanced Features

Email Content Extraction

International Character Support

Comprehensive Label Management

Batch Operations

Security Notes

Troubleshooting

Contributing

License

Support

For Tasks:

For Jobs:

Alternative AI tools for Gmail-MCP-Server

Similar Open Source Tools

Gmail-MCP-Server

context7

trapster-community

mcpdoc

shortest

ai-gateway

mcphub.nvim

clewdr

mcp-redis

llm-web-api

scylla

claim-ai-phone-bot

perplexity-mcp

snak

claude-task-master

mcp-victoriametrics

For similar tasks

Gmail-MCP-Server

UFO

For similar jobs

zep

doc2plan

whatsapp-chatgpt

OmniSteward

chatgpt-wechat

mcp-agent

Gmail-MCP-Server

Operit

1. Send Email (`send_email`)

2. Draft Email (`draft_email`)

3. Read Email (`read_email`)

4. Search Emails (`search_emails`)

5. Modify Email (`modify_email`)

6. Delete Email (`delete_email`)

7. List Email Labels (`list_email_labels`)

8. Create Label (`create_label`)

9. Update Label (`update_label`)

10. Delete Label (`delete_label`)

11. Get or Create Label (`get_or_create_label`)

12. Batch Modify Emails (`batch_modify_emails`)

13. Batch Delete Emails (`batch_delete_emails`)