abstractapi-mcp-server

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check_email_reputation

Analyze email reputation to assess deliverability, quality, risk, and breach history for improving email list hygiene and preventing fraud.

Instructions

Analyzes email reputation using Abstract API's Email Reputation service.

This function provides comprehensive email reputation analysis including deliverability,
quality scoring, sender information, domain details, risk assessment, and breach history.
It's designed to help improve delivery rates, clean email lists, and block fraudulent users.

Args:
    email (str): The email address to analyze for reputation.

Returns:
    dict[str, Any]: A dictionary containing comprehensive reputation analysis. The dictionary
    includes the following main sections:
        - "email_address" (str): The email address that was analyzed.
        - "email_deliverability" (dict): Deliverability information.
            - "status" (str): "deliverable", "undeliverable", or "unknown".
            - "status_detail" (str): Additional detail (e.g., "valid_email", "invalid_format").
            - "is_format_valid" (bool): True if email follows correct format.
            - "is_smtp_valid" (bool): True if SMTP check was successful.
            - "is_mx_valid" (bool): True if domain has valid MX records.
            - "mx_records" (list): List of MX records for the domain.
        - "email_quality" (dict): Quality assessment information.
            - "score" (float): Confidence score between 0.01 and 0.99.
            - "is_free_email" (bool): True if from free provider (Gmail, Yahoo, etc.).
            - "is_username_suspicious" (bool): True if username appears auto-generated.
            - "is_disposable" (bool): True if from disposable email provider.
            - "is_catchall" (bool): True if domain accepts all emails.
            - "is_subaddress" (bool): True if uses subaddressing (user+label@domain.com).
            - "is_role" (bool): True if role-based address (info@, support@, etc.).
            - "is_dmarc_enforced" (bool): True if strict DMARC policy enforced.
            - "is_spf_strict" (bool): True if domain enforces strict SPF policy.
            - "minimum_age" (int|null): Estimated age of email address in days.
        - "email_sender" (dict): Sender information if available.
            - "first_name" (str|null): First name associated with email.
            - "last_name" (str|null): Last name associated with email.
            - "email_provider_name" (str|null): Email provider name (e.g., "Google").
            - "organization_name" (str|null): Organization linked to email/domain.
            - "organization_type" (str|null): Type of organization (e.g., "company").
        - "email_domain" (dict): Domain information.
            - "domain" (str): Domain part of the email.
            - "domain_age" (int|null): Age of domain in days.
            - "is_live_site" (bool|null): True if domain has active website.
            - "registrar" (str|null): Domain registrar name.
            - "registrar_url" (str|null): Registrar website URL.
            - "date_registered" (str|null): Domain registration date.
            - "date_last_renewed" (str|null): Last renewal date.
            - "date_expires" (str|null): Domain expiration date.
            - "is_risky_tld" (bool|null): True if top-level domain is considered risky.
        - "email_risk" (dict): Risk assessment.
            - "address_risk_status" (str): Risk level for the email address.
            - "domain_risk_status" (str): Risk level for the domain.
        - "email_breaches" (dict): Data breach information.
            - "total_breaches" (int|null): Number of known breaches.
            - "date_first_breached" (str|null): Date of first known breach.
            - "date_last_breached" (str|null): Date of most recent breach.
            - "breached_domains" (list): List of breached domains with dates.

Example:
    >>> await check_email_reputation("benjamin.richard@abstractapi.com")
    {
        "email_address": "benjamin.richard@abstractapi.com",
        "email_deliverability": {
            "status": "deliverable",
            "status_detail": "valid_email",
            "is_format_valid": true,
            "is_smtp_valid": true,
            "is_mx_valid": true,
            "mx_records": ["gmail-smtp-in.l.google.com", ...]
        },
        "email_quality": {
            "score": 0.8,
            "is_free_email": false,
            "is_username_suspicious": false,
            "is_disposable": false,
            "is_catchall": true,
            "is_subaddress": false,
            "is_role": false,
            "is_dmarc_enforced": true,
            "is_spf_strict": true,
            "minimum_age": 1418
        },
        "email_sender": {
            "first_name": "Benjamin",
            "last_name": "Richard",
            "email_provider_name": "Google",
            "organization_name": "Abstract API",
            "organization_type": "company"
        },
        "email_domain": {
            "domain": "abstractapi.com",
            "domain_age": 1418,
            "is_live_site": true,
            "registrar": "NAMECHEAP INC",
            "registrar_url": "http://www.namecheap.com",
            "date_registered": "2020-05-13",
            "date_last_renewed": "2024-04-13",
            "date_expires": "2025-05-13",
            "is_risky_tld": false
        },
        "email_risk": {
            "address_risk_status": "low",
            "domain_risk_status": "low"
        },
        "email_breaches": {
            "total_breaches": 2,
            "date_first_breached": "2018-07-23T14:30:00Z",
            "date_last_breached": "2019-05-24T14:30:00Z",
            "breached_domains": [
                {"domain": "apollo.io", "date_breached": "2018-07-23T14:30:00Z"},
                {"domain": "canva.com", "date_breached": "2019-05-24T14:30:00Z"}
            ]
        }
    }

Raises:
    ValueError: If the API key is not found in the environment variables.
    requests.exceptions.HTTPError: If the API request fails (e.g., 4xx or 5xx error).
    Exception: For any other unexpected errors.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`email`	Yes

Implementation Reference

server.py:219-364 (handler)

The core handler function decorated with @mcp.tool(), which registers and implements the check_email_reputation tool. It validates the presence of the API key, constructs the API request to Abstract API's Email Reputation endpoint, fetches and returns the reputation data as a dictionary, with comprehensive error handling.

@mcp.tool()
async def check_email_reputation(email: str) -> dict[str, Any]:
    """
    Analyzes email reputation using Abstract API's Email Reputation service.

    This function provides comprehensive email reputation analysis including deliverability,
    quality scoring, sender information, domain details, risk assessment, and breach history.
    It's designed to help improve delivery rates, clean email lists, and block fraudulent users.

    Args:
        email (str): The email address to analyze for reputation.

    Returns:
        dict[str, Any]: A dictionary containing comprehensive reputation analysis. The dictionary
        includes the following main sections:
            - "email_address" (str): The email address that was analyzed.
            - "email_deliverability" (dict): Deliverability information.
                - "status" (str): "deliverable", "undeliverable", or "unknown".
                - "status_detail" (str): Additional detail (e.g., "valid_email", "invalid_format").
                - "is_format_valid" (bool): True if email follows correct format.
                - "is_smtp_valid" (bool): True if SMTP check was successful.
                - "is_mx_valid" (bool): True if domain has valid MX records.
                - "mx_records" (list): List of MX records for the domain.
            - "email_quality" (dict): Quality assessment information.
                - "score" (float): Confidence score between 0.01 and 0.99.
                - "is_free_email" (bool): True if from free provider (Gmail, Yahoo, etc.).
                - "is_username_suspicious" (bool): True if username appears auto-generated.
                - "is_disposable" (bool): True if from disposable email provider.
                - "is_catchall" (bool): True if domain accepts all emails.
                - "is_subaddress" (bool): True if uses subaddressing (user+label@domain.com).
                - "is_role" (bool): True if role-based address (info@, support@, etc.).
                - "is_dmarc_enforced" (bool): True if strict DMARC policy enforced.
                - "is_spf_strict" (bool): True if domain enforces strict SPF policy.
                - "minimum_age" (int|null): Estimated age of email address in days.
            - "email_sender" (dict): Sender information if available.
                - "first_name" (str|null): First name associated with email.
                - "last_name" (str|null): Last name associated with email.
                - "email_provider_name" (str|null): Email provider name (e.g., "Google").
                - "organization_name" (str|null): Organization linked to email/domain.
                - "organization_type" (str|null): Type of organization (e.g., "company").
            - "email_domain" (dict): Domain information.
                - "domain" (str): Domain part of the email.
                - "domain_age" (int|null): Age of domain in days.
                - "is_live_site" (bool|null): True if domain has active website.
                - "registrar" (str|null): Domain registrar name.
                - "registrar_url" (str|null): Registrar website URL.
                - "date_registered" (str|null): Domain registration date.
                - "date_last_renewed" (str|null): Last renewal date.
                - "date_expires" (str|null): Domain expiration date.
                - "is_risky_tld" (bool|null): True if top-level domain is considered risky.
            - "email_risk" (dict): Risk assessment.
                - "address_risk_status" (str): Risk level for the email address.
                - "domain_risk_status" (str): Risk level for the domain.
            - "email_breaches" (dict): Data breach information.
                - "total_breaches" (int|null): Number of known breaches.
                - "date_first_breached" (str|null): Date of first known breach.
                - "date_last_breached" (str|null): Date of most recent breach.
                - "breached_domains" (list): List of breached domains with dates.

    Example:
        >>> await check_email_reputation("benjamin.richard@abstractapi.com")
        {
            "email_address": "benjamin.richard@abstractapi.com",
            "email_deliverability": {
                "status": "deliverable",
                "status_detail": "valid_email",
                "is_format_valid": true,
                "is_smtp_valid": true,
                "is_mx_valid": true,
                "mx_records": ["gmail-smtp-in.l.google.com", ...]
            },
            "email_quality": {
                "score": 0.8,
                "is_free_email": false,
                "is_username_suspicious": false,
                "is_disposable": false,
                "is_catchall": true,
                "is_subaddress": false,
                "is_role": false,
                "is_dmarc_enforced": true,
                "is_spf_strict": true,
                "minimum_age": 1418
            },
            "email_sender": {
                "first_name": "Benjamin",
                "last_name": "Richard",
                "email_provider_name": "Google",
                "organization_name": "Abstract API",
                "organization_type": "company"
            },
            "email_domain": {
                "domain": "abstractapi.com",
                "domain_age": 1418,
                "is_live_site": true,
                "registrar": "NAMECHEAP INC",
                "registrar_url": "http://www.namecheap.com",
                "date_registered": "2020-05-13",
                "date_last_renewed": "2024-04-13",
                "date_expires": "2025-05-13",
                "is_risky_tld": false
            },
            "email_risk": {
                "address_risk_status": "low",
                "domain_risk_status": "low"
            },
            "email_breaches": {
                "total_breaches": 2,
                "date_first_breached": "2018-07-23T14:30:00Z",
                "date_last_breached": "2019-05-24T14:30:00Z",
                "breached_domains": [
                    {"domain": "apollo.io", "date_breached": "2018-07-23T14:30:00Z"},
                    {"domain": "canva.com", "date_breached": "2019-05-24T14:30:00Z"}
                ]
            }
        }

    Raises:
        ValueError: If the API key is not found in the environment variables.
        requests.exceptions.HTTPError: If the API request fails (e.g., 4xx or 5xx error).
        Exception: For any other unexpected errors.
    """
    # Check if the API key is available
    if not ABSTRACT_API_KEY:
        raise ValueError("API key not found in environment variables.")

    # Construct the API URL
    api_url = f"{EMAIL_REPUTATION_API_URL}?api_key={ABSTRACT_API_KEY}&email={email}"

    try:
        # Make the API request (ignoring SSL verification)
        response = requests.get(api_url, verify=False)
        response.raise_for_status()  # Raise an error for bad responses (4xx, 5xx)

        # Parse the JSON response
        result = response.json()

        # Return the reputation analysis results
        return result

    except requests.exceptions.HTTPError as http_err:
        # Handle HTTP errors (e.g., 4xx, 5xx)
        raise requests.exceptions.HTTPError(f"HTTP error occurred: {http_err}")
    except Exception as err:
        # Handle any other errors
        raise Exception(f"An error occurred: {err}")

server.py:219-219 (registration)
The @mcp.tool() decorator registers the check_email_reputation function as an MCP tool.
```
@mcp.tool()
```

server.py:220-339 (schema)

The function signature provides type hints for input (email: str) and output (dict[str, Any]). The extensive docstring details the expected output structure including email_deliverability, email_quality, email_sender, email_domain, email_risk, and email_breaches sections.

async def check_email_reputation(email: str) -> dict[str, Any]:
    """
    Analyzes email reputation using Abstract API's Email Reputation service.

    This function provides comprehensive email reputation analysis including deliverability,
    quality scoring, sender information, domain details, risk assessment, and breach history.
    It's designed to help improve delivery rates, clean email lists, and block fraudulent users.

    Args:
        email (str): The email address to analyze for reputation.

    Returns:
        dict[str, Any]: A dictionary containing comprehensive reputation analysis. The dictionary
        includes the following main sections:
            - "email_address" (str): The email address that was analyzed.
            - "email_deliverability" (dict): Deliverability information.
                - "status" (str): "deliverable", "undeliverable", or "unknown".
                - "status_detail" (str): Additional detail (e.g., "valid_email", "invalid_format").
                - "is_format_valid" (bool): True if email follows correct format.
                - "is_smtp_valid" (bool): True if SMTP check was successful.
                - "is_mx_valid" (bool): True if domain has valid MX records.
                - "mx_records" (list): List of MX records for the domain.
            - "email_quality" (dict): Quality assessment information.
                - "score" (float): Confidence score between 0.01 and 0.99.
                - "is_free_email" (bool): True if from free provider (Gmail, Yahoo, etc.).
                - "is_username_suspicious" (bool): True if username appears auto-generated.
                - "is_disposable" (bool): True if from disposable email provider.
                - "is_catchall" (bool): True if domain accepts all emails.
                - "is_subaddress" (bool): True if uses subaddressing (user+label@domain.com).
                - "is_role" (bool): True if role-based address (info@, support@, etc.).
                - "is_dmarc_enforced" (bool): True if strict DMARC policy enforced.
                - "is_spf_strict" (bool): True if domain enforces strict SPF policy.
                - "minimum_age" (int|null): Estimated age of email address in days.
            - "email_sender" (dict): Sender information if available.
                - "first_name" (str|null): First name associated with email.
                - "last_name" (str|null): Last name associated with email.
                - "email_provider_name" (str|null): Email provider name (e.g., "Google").
                - "organization_name" (str|null): Organization linked to email/domain.
                - "organization_type" (str|null): Type of organization (e.g., "company").
            - "email_domain" (dict): Domain information.
                - "domain" (str): Domain part of the email.
                - "domain_age" (int|null): Age of domain in days.
                - "is_live_site" (bool|null): True if domain has active website.
                - "registrar" (str|null): Domain registrar name.
                - "registrar_url" (str|null): Registrar website URL.
                - "date_registered" (str|null): Domain registration date.
                - "date_last_renewed" (str|null): Last renewal date.
                - "date_expires" (str|null): Domain expiration date.
                - "is_risky_tld" (bool|null): True if top-level domain is considered risky.
            - "email_risk" (dict): Risk assessment.
                - "address_risk_status" (str): Risk level for the email address.
                - "domain_risk_status" (str): Risk level for the domain.
            - "email_breaches" (dict): Data breach information.
                - "total_breaches" (int|null): Number of known breaches.
                - "date_first_breached" (str|null): Date of first known breach.
                - "date_last_breached" (str|null): Date of most recent breach.
                - "breached_domains" (list): List of breached domains with dates.

    Example:
        >>> await check_email_reputation("benjamin.richard@abstractapi.com")
        {
            "email_address": "benjamin.richard@abstractapi.com",
            "email_deliverability": {
                "status": "deliverable",
                "status_detail": "valid_email",
                "is_format_valid": true,
                "is_smtp_valid": true,
                "is_mx_valid": true,
                "mx_records": ["gmail-smtp-in.l.google.com", ...]
            },
            "email_quality": {
                "score": 0.8,
                "is_free_email": false,
                "is_username_suspicious": false,
                "is_disposable": false,
                "is_catchall": true,
                "is_subaddress": false,
                "is_role": false,
                "is_dmarc_enforced": true,
                "is_spf_strict": true,
                "minimum_age": 1418
            },
            "email_sender": {
                "first_name": "Benjamin",
                "last_name": "Richard",
                "email_provider_name": "Google",
                "organization_name": "Abstract API",
                "organization_type": "company"
            },
            "email_domain": {
                "domain": "abstractapi.com",
                "domain_age": 1418,
                "is_live_site": true,
                "registrar": "NAMECHEAP INC",
                "registrar_url": "http://www.namecheap.com",
                "date_registered": "2020-05-13",
                "date_last_renewed": "2024-04-13",
                "date_expires": "2025-05-13",
                "is_risky_tld": false
            },
            "email_risk": {
                "address_risk_status": "low",
                "domain_risk_status": "low"
            },
            "email_breaches": {
                "total_breaches": 2,
                "date_first_breached": "2018-07-23T14:30:00Z",
                "date_last_breached": "2019-05-24T14:30:00Z",
                "breached_domains": [
                    {"domain": "apollo.io", "date_breached": "2018-07-23T14:30:00Z"},
                    {"domain": "canva.com", "date_breached": "2019-05-24T14:30:00Z"}
                ]
            }
        }

    Raises:
        ValueError: If the API key is not found in the environment variables.
        requests.exceptions.HTTPError: If the API request fails (e.g., 4xx or 5xx error).
        Exception: For any other unexpected errors.
    """

server.py:16-19 (helper)

Constants used by the tool: API endpoint URL and API key loaded from environment.

ABSTRACT_API_KEY = os.getenv("ABSTRACT_API_KEY", "your_api_key_here")
ABSTRACT_API_URL = "https://emailvalidation.abstractapi.com/v1/"
PHONE_VALIDATION_API_URL = "https://phonevalidation.abstractapi.com/v1/"
EMAIL_REPUTATION_API_URL = "https://emailreputation.abstractapi.com/v1/"

Tool Definition Quality

A4.2/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden and does well by disclosing behavioral traits: it explains the comprehensive analysis scope, mentions API dependencies (Abstract API), and includes error handling details in the 'Raises' section. However, it doesn't mention rate limits, authentication requirements beyond the API key error, or whether this is a read-only operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately front-loaded with purpose and usage, but becomes overly verbose with an extremely detailed example (60+ lines) that duplicates information already implied by the return structure description. The 'Raises' section is useful but could be more concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (comprehensive reputation analysis), no annotations, and no output schema, the description provides exceptional completeness: detailed purpose, parameter semantics, comprehensive return structure documentation, example output, and error handling. Nothing essential is missing for agent understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage and only one parameter, the description compensates fully by providing detailed semantics for the 'email' parameter in the Args section, explaining it's 'The email address to analyze for reputation' with clear type information and usage context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool 'analyzes email reputation using Abstract API's Email Reputation service' with specific verbs ('analyzes', 'provides comprehensive analysis') and distinguishes it from sibling tools (validate_phone, verify_email) by focusing on reputation analysis rather than validation or verification.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context ('designed to help improve delivery rates, clean email lists, and block fraudulent users') but doesn't explicitly state when to use this tool versus the sibling tools (validate_phone, verify_email). No explicit alternatives or exclusions are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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