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OpenOSINT

OpenOSINT

by kush-coder
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

graph_export

Exports the OpenOSINT FollowTheMoney entity graph to newline-delimited JSON for .ftm-compatible use, with optional dataset exclusion to omit breach-derived facts.

Instructions

Export the additive FollowTheMoney entity graph (openosint.graph) as newline-delimited JSON, one FtM entity per line (.ftm-compatible). Optionally exclude whole datasets, e.g. exclude_datasets=['openosint:hibp'] to omit every breach-derived fact. Requires the 'graph' extra: pip install 'openosint[graph]'. [passive] Reads the local graph database only.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "graph_export"
  }
}

Input Schema

NameRequiredDescriptionDefault
json_outputNoReturn result as structured JSON.
exclude_datasetsNoDataset names to omit entirely, e.g. ['openosint:hibp'].

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.36.1

TDQS

A4.2/5.0
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 largely succeeds: it declares [passive], states it reads the local graph database only, specifies the install dependency, and explains what exclusion does (omit every breach-derived fact). It is silent on scale/streaming behavior for a potentially huge graph, which keeps it below 5.

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 core action and output format are front-loaded, and each subsequent sentence adds distinct value (exclusion semantics, dependency requirement, read-only scope). No filler.

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?

Without annotations or an output schema, the description must supply the behavioral and output contract, and it does describe the line format and .ftm compatibility. Remaining gaps are secondary details like error behavior when the extra is missing or handling of very large graphs.

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?

Schema coverage is already 100%, so the baseline is 3; the description adds real meaning by giving a worked example for exclude_datasets ('openosint:hibp') and clarifying that whole datasets are omitted, including derived facts. json_output is left to the 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?

States a specific verb (export), a specific resource (the additive FollowTheMoney entity graph / openosint.graph), and the exact output format (newline-delimited JSON, one FtM entity per line). This is clearly distinguishable from the search_* and graph_neighbors siblings, which query rather than bulk-export.

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?

Conveys usage context (bulk export for downstream .ftm tooling, reads the local DB only, needs the 'graph' extra) and a concrete exclusion example, but never states when to prefer this over graph_neighbors or graph_review_candidates, nor any when-not conditions. Usage is implied rather than spelled out.

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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