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OpenOSINT

by kush-coder
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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search_footprint

Collect a target's public search-engine footprint by detecting its entity type and running targeted Google queries, returning structured results and correlation graph data.

Instructions

Collect a target's public search-engine footprint via the Bright Data SERP API. Detects entity type (email, username, domain, phone, or full name) and runs entity-type-aware Google queries, returning structured results and Entity Correlation Graph nodes/edges for discovered domains and profiles. Uses BRIGHTDATA_API_KEY and BRIGHTDATA_SERP_ZONE env vars. [passive] Up to 3 Google queries via Bright Data; the target is sent to those two services.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "target": "<target>"
    },
    "name": "search_footprint"
  }
}

Input Schema

NameRequiredDescriptionDefault
targetYes
json_outputNoReturn result as structured JSON.
max_queriesNoMax SERP queries (default 3, each is billable).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.36.1

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does disclose key behaviors: it is passive, requires BRIGHTDATA_API_KEY and BRIGHTDATA_SERP_ZONE, is capped at up to 3 Google queries, and warns that the target is sent to external services. It falls short of 5 only by not covering failure modes, error handling, or how partial results are surfaced.

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 core purpose and output are front-loaded, and the bracketed [passive] and env-var/billing details are dense but each earns its place. Slightly information-heavy for a single sentence, but not padded.

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?

There is no output schema, so the description correctly explains what comes back (structured SERP results plus graph nodes/edges), and with no annotations it covers auth, cost, and passivity. It is nearly complete; only the 'target' semantics and error behavior could be made more explicit.

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

Parameters4/5

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

The schema leaves 'target' entirely undescribed, and the description compensates by enumerating accepted entity types (email, username, domain, phone, full name). It also ties max_queries' 'up to 3' to actual Google query behavior, though json_output is not addressed. This adds real meaning beyond the 67% schema coverage.

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?

States a specific verb and resource ('Collect a target's public search-engine footprint via the Bright Data SERP API') and details entity-type detection plus SERP and graph-node output. It is clearly distinguishable in substance, but never names or contrasts against the closely related siblings (search_dorks_live, generate_dorks), so it stops short of full sibling differentiation.

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

Usage Guidelines3/5

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

Usage is only implied by the purpose ('to footprint a target'). There is no explicit when-to-use, no when-not-to-use, and no routing to the adjacent tools (search_dorks_live, generate_dorks) that also issue Google queries, leaving the agent to infer which tool fits.

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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