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scalably-io

Hunter MCP

by scalably-io

discover

Read-only

Find companies by natural-language or structured criteria such as location, industry, headcount, funding, technology, keywords, organization, and company type to build targeted prospect lists.

Instructions

Use Hunter Discover v2 to find companies from current natural-language or structured organization, location, industry, headcount, type, year, keyword, technology, and funding filters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryNo
offsetNo
fundingNo
industryNo
keywordsNo
headcountNo
similar_toNo
technologyNo
company_typeNo
organizationNo
year_foundedNo
headquarters_locationNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is established. The description adds 'current' data and lists filter categories, but it does not disclose return behavior, pagination defaults, result limits, or matching semantics such as include/exclude/match behavior.

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

Conciseness4/5

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

The description is a single front-loaded sentence with no filler. It gives the action and resource first, then lists filters compactly. It is appropriately sized for a summary, though it could add more value with a few targeted usage details.

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?

This is a high-complexity tool: 13 optional parameters, nested objects, no required parameters, no output schema, and zero parameter descriptions. The description only provides a high-level filter summary and leaves out essential operational context like how the query parameter interacts with structured filters, pagination, and what the response contains.

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

Parameters3/5

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

With 0% schema description coverage, the description partially compensates by naming the main filter groups: organization, location, industry, headcount, type, year, keyword, technology, and funding. However, it omits parameter semantics for limit, offset, similar_to, and the include/exclude/match structures, so the compensation is incomplete.

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

Purpose4/5

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

The description clearly states the action ('find companies') and the resource ('Hunter Discover v2'), and it enumerates the main filter dimensions. It does not explicitly differentiate from sibling tools like company_enrichment or domain_search, but the 'find companies' framing and filter list make the core purpose reasonably distinct.

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?

No guidance is given about when to use Discover compared with sibling tools such as company_enrichment, domain_search, or email_finder. The description implies broad company discovery use, but it does not state exclusions, prerequisites, or alternative routing.

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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