Skip to main content
Glama
hunter-io

Hunter MCP Server

Official
by hunter-io

email_finder

Find professional email addresses by entering a domain and full name to connect with business contacts.

Instructions

Return the most likely email address for a given domain and full name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYes
full_nameYes

Implementation Reference

  • main.py:20-24 (handler)
    The handler function implementing the 'email_finder' MCP tool. It constructs parameters from inputs and calls the Hunter API's email-finder endpoint using the HunterAPIClient.
    @mcp.tool(description="Return the most likely email address for a given domain and full name.")
    async def email_finder(domain: str, full_name: str) -> str:
        async with HunterAPIClient() as client:
            response = await client.get("email-finder", {"domain": domain, "full_name": full_name})
            return response
Behavior2/5

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

With no annotations provided, the description carries full burden but only states what the tool does without disclosing behavioral traits such as rate limits, accuracy, data sources, or error handling. It mentions 'most likely' email but doesn't explain confidence levels or fallback behaviors.

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

Conciseness5/5

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

The description is a single, efficient sentence that front-loads the core purpose with zero waste. It is appropriately sized for a simple tool and avoids unnecessary elaboration.

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

Completeness2/5

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

Given no annotations, 0% schema coverage, and no output schema, the description is incomplete for a tool that infers emails—it lacks details on return values (e.g., email format, confidence scores), error cases, or integration context with siblings. It provides minimal context beyond the basic action.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate but only mentions parameters generically ('domain and full name') without adding meaning like format examples (e.g., 'example.com' for domain, 'John Doe' for full name) or constraints. It fails to provide semantic details beyond the bare schema.

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's purpose with specific verb ('Return') and resource ('most likely email address'), specifying the input parameters ('domain and full name'). It distinguishes from siblings like 'email_verifier' (which likely verifies rather than finds) and 'domain_search' (which may search domains without names).

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

Usage Guidelines2/5

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 like 'enrich_email' or 'create_lead', nor does it mention prerequisites or exclusions. It implies usage for finding emails but lacks explicit context for tool selection.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/hunter-io/hunter-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server