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Model Context Protocol (MCP): Email Validation & Instant Checks - MCP Implementation

Model Context Protocol (MCP): Email Validation & Instant Checks

Streamline email validation for AI apps with MCP: Lightweight server instantly checks format, domain, and deliverability via AbstractAPI. Perfect for LLMs like Claude Desktop.

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About Model Context Protocol (MCP)

What is Model Context Protocol (MCP): Email Validation & Instant Checks?

Model Context Protocol (MCP) is a standardized communication framework enabling AI models to interface with external systems in real-time. This implementation focuses on email validation, offering instant checks for syntax accuracy, domain verification, and deliverability assessment. By integrating MCP, developers can seamlessly embed robust email validation directly into their AI workflows without manual configuration.

Key Features of Model Context Protocol (MCP): Email Validation & Instant Checks

  • Real-time syntax validation for email format compliance
  • Domain MX record checks to confirm deliverability
  • Pre-configured MCP integration for rapid deployment
  • Automated error handling with detailed diagnostic outputs
  • Support for batch validation of multiple email addresses

Model Context Protocol (MCP) Features

How to Use Model Context Protocol (MCP): Email Validation & Instant Checks

  1. Initialize the MCP client with your API credentials
  2. Pass email addresses through the validation endpoint
  3. Receive structured responses containing:
    • Format validation status
    • Domain reputation score
    • Disposable email detection
  4. Integrate results directly into forms, user onboarding, or CRM systems

Use Cases of Model Context Protocol (MCP): Email Validation & Instant Checks

Common applications include:

  • User registration systems to prevent invalid email submissions
  • Customer support platforms for verified contact tracking
  • Email marketing campaigns to maintain clean subscriber lists
  • API gateways requiring strict input validation protocols
  • Automated report delivery systems ensuring recipient reachability

Model Context Protocol (MCP) FAQ

FAQ from Model Context Protocol (MCP): Email Validation & Instant Checks

Q: What technical requirements are needed?

A: Requires Python 3.8+, valid API key, and internet connectivity. Works natively with popular frameworks like Flask/Django.

Q: How are API limits managed?

A: Includes tiered rate limiting with burst allowances. Free tier supports 1000 checks/month, scalable enterprise plans available.

Q: Can this validate international domains?

A: Fully supports non-ASCII characters and regional TLDs (e.g., .jp, .cn, .br) through Unicode normalization.

Q: Does it check mailbox existence?

A: Uses SMTP validation for final verification step, with optional risk scoring for potential temporary failures.

Content

MCP Email Verify

A lightweight Model Context Protocol (MCP) server that enables your LLM to validate email addresses. This tool checks email format, domain validity, and deliverability using the AbstractAPI Email Validation API. Perfect for integrating email validation into AI applications like Claude Desktop.


What is Model Context Protocol (MCP)?

At its core, MCP is a standardized protocol designed to streamline communication between AI models and external systems. Think of it as a universal language that allows different AI agents, tools, and services to interact seamlessly.

MCP drawio \(1\)


Features

  • Email Verification : Verify email addresses in real-time.
  • MCP Integration : Seamlessly connect with MCP-compatible LLMs.
  • Easy Setup : Built with Python and the MCP SDK for quick deployment.

MCP follows a client-server architecture:

client server drawio


Watch the Demo

Click the image below to watch a video demo of the MCP Email Verify tool in action:

Screenshot 2025-03-23 115525


Requirements

  • Python : Python 3.11.0 or higher.
  • UV : 0.6.9 or higher.

Setup

1. Clone the Repository

git clone https://github.com/Abhi5h3k/MCP-Email-Verify.git
cd MCP-Email-Verify

2. Install UV

If you don’t have UV installed, you can install it using the following commands:

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Verify the installation:

uv --version

3. Set Up the Virtual Environment

Create a virtual environment using UV:

uv venv

Activate the virtual environment: On Windows:

.venv\Scripts\activate

4. Install Dependencies Install the required dependencies from pyproject.toml using UV:

uv install

Running the Server

  1. Set Up Environment Variables Create a .env file in the root directory and add your AbstractAPI key:
ABSTRACT_API_KEY=your_api_key_here
  1. Run the Server Start the MCP server:
uv run server.py

Usage

  1. Register the Server with Claude Desktop Update the claude_desktop_config.json file to include your MCP server:
{
    "mcpServers": {
        "verify_mail": {
            "command": "uv",
            "args": [
                "--directory",
                "C:\\ABSOLUTE\\PATH\\TO\\MCP-Email-Verify",
                "run",
                "server.py"
            ]
        }
    }
}

image

  1. Restart Claude Desktop Restart Claude Desktop to detect the new tool.

  2. Verify Emails Use prompts like:

"I was trying to email Thanos at [email protected] to ask him to bring back my favorite TV show, but I’m not sure if it’s a valid email. Can you check if it’s real or just a snap in the dark?"

Development

Formatting and Linting This project uses black and isort for code formatting and import sorting.

  1. Install development dependencies:

    uv add black isort --dev
    
  2. Format the code:

    black .

  3. Sort imports:

    isort .

Set up pre-commit

pre-commit install
pre-commit run --all-files

Available On Smithery.ai Server: MCP Email Verify

Article: Model Context Protocol (MCP): A Beginner's Guide to the Future of AI Communication

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