Email Checker MCP Server
The Email Checker MCP Server validates email addresses for cold outbound email campaigns.
Verify if an email address exists (returns "true" or "false")
Uses the 2ip.me API without requiring an API key
Handles various errors including invalid formats, API failures, network timeouts, and rate limiting
Configurable as an MCP server for integration with Claude desktop
Can run validation through FastMCP tool with async functionality
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Email Checker MCP Servercheck if john.doe@example.com is a valid email"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Email Checker MCP Server
For your cold outbound email, this tool will help you validate email addresses.
Features
Email address validation
Simple JSON response format
No API key required
Related MCP server: email-verify
Prerequisites
Python 3.x
Installation
Clone the repository:
git clone https://github.com/ravinahp/email-checker-mcp.git
cd email-checker-mcpInstall dependencies using uv:
uv syncNote: We use uv instead of pip since the project uses pyproject.toml for dependency management.
Configure as MCP Server
To add this tool as an MCP server, you'll need to modify your Claude desktop configuration file.
The configuration file location depends on your operating system:
MacOS:
~/Library/Application\ Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%/Claude/claude_desktop_config.json
Add the following configuration to your JSON file:
{
"email-checker-mcp": {
"command": "uv",
"args": [
"--directory",
"/Users/YOUR_USERNAME/Code/email-checker-mcp",
"run",
"email-checker-mcp"
]
}
}⚠️ IMPORTANT:
Replace
YOUR_USERNAMEwith your actual system usernameMake sure the directory path matches your local installation
Usage
The service provides a FastMCP tool for validating email addresses:
@mcp.tool()
async def validate_email(email: str) -> bool:
"""Validate if an email address exists."""Example Use:
Prompt: Does this email exist?
Parameters:
email: String containing the email address to validate
Example Response:
{
"exist": true
}API Usage Limits
The service uses 2IP's Email API which provides:
No API key required
Error Handling
The service includes error handling for:
Invalid email format
API request failures
Network timeouts
Rate limiting
Available Tools
1 toolverify_emailB
Verify an email address using the 2ip.me API.
Args:
email (str): The email address to verify
Returns:
str: "true" or "false" indicating if the email is valid
| Name | Required | Description | Default |
|---|---|---|---|
| Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the API source (2ip.me) and the return value format, but it lacks details on rate limits, authentication needs, error handling, or what 'valid' means (e.g., syntax check vs. deliverability). This leaves significant gaps for a tool that interacts with an external service.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and concise, with three sentences that efficiently cover the purpose, input, and output. Each sentence adds value: the first states the action and API, the second defines the parameter, and the third explains the return value. There is no wasted verbiage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is moderately complete. It covers the basic purpose and return format but lacks behavioral details like error cases or API limitations. Without annotations or output schema, it should ideally include more about what 'valid' entails or usage constraints, leaving room for improvement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context beyond the input schema. The schema has 0% description coverage, but the description specifies that the 'email' parameter is 'The email address to verify,' clarifying its purpose. Since there's only one parameter, this adequately compensates for the low schema coverage, though it doesn't detail format constraints (e.g., valid email patterns).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Verify an email address using the 2ip.me API.' It specifies the verb ('verify') and resource ('email address'), though it doesn't differentiate from siblings since there are none. The description is specific but lacks the nuance of sibling differentiation that would warrant a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It states what the tool does but offers no context about prerequisites, limitations, or scenarios for its application. With no siblings, it could implicitly be the only option, but explicit usage guidelines are missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
- First observed
verify_email
TDQS
Scored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined and distinct.
Since there is only one tool, naming consistency is inherently perfect. The tool name 'verify_email' follows a clear verb_noun pattern.
A single tool is too few for a server named 'Email Checker MCP Server', which suggests a broader scope. This minimal set feels thin and underdeveloped for the domain.
The server is severely incomplete for email checking. It only verifies email validity, missing obvious operations like checking email deliverability, domain reputation, or spam score, which are typical in this domain.
Maintenance
Related MCP Connectors
Keyless email checks: disposable, role, and free-provider detection, MX, and typo suggestions.
Email validation for Claude and any MCP client — verdicts with evidence, bulk jobs, refunds.
Emailable MCP — wraps the Emailable email verification API (emailable.com)
Fast email validation at the edge: syntax, MX records, disposable-domain detection.
Related MCP Servers
- AlicenseAqualityCmaintenanceEmail validation MCP server using MailboxValidator API to determine validity of an email address.334 npm1MIT
- AlicenseAqualityDmaintenanceEnables real-time email verification via MCP tools, checking syntax, MX, disposable domains, and optional SMTP probe to determine deliverability with a VALID/RISKY/INVALID verdict.25 npmMIT
- FlicenseBqualityCmaintenanceAn MCP server that provides email verification, returning valid, invalid, or risky status with detailed checks and metadata. It enables verifying email addresses via a simple tool interface.3-
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