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osint-toolbox-mcp

theHarvester domain search

theharvester_domain_search
Read-onlyIdempotent

Gather email addresses, subdomains, hosts, IP addresses, and URLs for a domain or company from public OSINT sources.

Instructions

Collect email addresses, subdomains, hosts, IP addresses and URLs for a domain or company name from public sources (theHarvester).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results (default: 500)
domainYesDomain (example.com) or company name
sourcesNoComma-separated sources, e.g. crtsh,duckduckgo,hackertarget (default: all; sources that need an API key are skipped unless the key is in theHarvester's api-keys.yaml)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.1

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, so the safety profile is covered. The description adds that data comes from 'public sources', hinting at external queries, but does not disclose potential rate limits, network latencies, or result unpredictability beyond the openWorldHint. This is adequate but not rich.

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, front-loaded sentence that efficiently communicates the tool's purpose and output. There is no redundant filler or repetition of schema details.

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

Completeness4/5

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

For a read-only recon tool with rich annotations and fully documented parameters, the description is nearly complete. It covers what data is collected and from where. It does not describe the output structure or potential empty-result behavior, but the annotations and schema already carry much of the burden, and the listed data types imply the return content.

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?

Schema description coverage is 100%, so every parameter (domain, limit, sources) is already documented in the schema. The tool description adds context about domain or company name input and the variety of output data, but it does not add significant parameter-level semantics beyond what the schema provides. Baseline 3 is appropriate.

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 states a specific action ('Collect') and a clear resource ('email addresses, subdomains, hosts, IP addresses and URLs for a domain or company name'). It also names the data source ('public sources') and the underlying tool (theHarvester). This clearly distinguishes it from sibling tools that search by username, email, phone, or scan infrastructure.

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

Usage Guidelines4/5

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

The description makes it clear the tool is for domain or company name reconnaissance, which implies when to use it relative to siblings like sherlock_username_search or holehe_email_search. It does not explicitly mention when not to use it or name an alternative, but the context and resource scope provide clear usage guidance.

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