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Shodan Internetdb

by io.github.pipeworx-io

Lookup Ip

lookup_ip
Read-onlyIdempotent

Look up an IP address in the Shodan InternetDB. Returns open ports, hostnames, known vulnerabilities (CVEs), CPEs (software identifiers), and tags. Free, no API key needed. Example: lookup_ip("8.8.8.8").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ipYesIPv4 address to look up (e.g., "8.8.8.8")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
ipYesThe IPv4 address that was looked up
cpesYesList of CPE software identifiers found on the IP address
tagsYesList of tags associated with the IP address
foundYesWhether the IP address was found in Shodan InternetDB
portsYesList of open ports found on the IP address
vulnsYesList of known CVE vulnerabilities for the IP address
hostnamesYesList of hostnames associated with the IP address

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds value by detailing the output (open ports, hostnames, CVEs, CPEs, tags) and clarifying the tool is free and requires no authentication. No contradictions with annotations.

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 extremely concise: two sentences plus an example. Every sentence adds unique information (purpose, returns, free/example). No fluff or redundancy.

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?

Given the tool's simplicity (1 parameter, output schema exists), the description is sufficiently complete. It explains what the tool returns, that it's free, and provides an example. No missing critical context for an AI agent.

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% with the single 'ip' parameter already described. The description reinforces this by showing an example ('8.8.8.8') and clarifying it's an IPv4 address, providing marginal extra semantics.

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 looks up an IP address in the Shodan InternetDB, specifying the resource (IP address) and the database, with a specific verb ('look up'). It lists the returned data (open ports, hostnames, CVEs, etc.), distinguishing it from sibling tools like 'ai_visibility_check' or 'resolve_entity' which serve different purposes.

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 includes practical usage guidance: 'Free, no API key needed' and an example call. It does not explicitly state when not to use this tool or name alternatives, but the context of siblings (none similar) makes this omission minor.

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

All Shodan Internetdb toolsInspect
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TDQS

A3.9/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, ask_pipeworx_grounded and deep_research both answer grounded research questions, and bet_research, polymarket_edges, and polymarket_arbitrage all surface prediction-market opportunities. Long descriptions help, but the overlap creates real misselection risk, especially between the ask_pipeworx variants.

Naming Consistency4/5

Most tools follow a clear lowercase snake_case verb_noun or domain_verb pattern (lookup_ip, resolve_entity, validate_claim, list_subscriptions, generate_llms_txt). There are minor deviations like noun-first names (entity_profile, polymarket_edges, pipeworx_trending) and product-branded verbs (ask_pipeworx), but the overall style is consistent enough to predict behavior.

Tool Count2/5

32 tools is well over the 25-tool threshold where a tool set becomes hard to navigate, and the server named 'Shodan Internetdb' carries only one Shodan-related tool among dozens of Pipeworx, Polymarket, memory, and utility tools. The count reflects scope sprawl rather than a focused, coherent surface.

Completeness3/5

The broader inferred domain (structured data lookup, entity research, prediction markets, memory, subscriptions) is covered surprisingly well, with lifecycle tools for subscriptions and memory. However, there are notable gaps: no tool to fetch a pipeworx:// citation URI directly, no equivalent scan coverage for non-NPM ecosystems despite mentioning them, and the Shodan surface is minimal relative to the server name.

Resources