AI Training Data Broker

Guidance on selling or licensing company data to AI labs: deal steps, de-identification, compliance.

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Qualität und Sicherheit

A
Qualität der Beschreibung
100%
Vollständigkeit des Schemas
98%
Qualität der Benennung
96%
Risiko der Vergiftung
100%
Übereinstimmung der Berechtigungen
90%
Einhaltung des Protokolls
100%

Befunde (1)

  • LOWTool 'fetch' suggests web access but openWorldHint=falsein fetch

Basierend auf einer automatisierten Analyse der Tool-Definitionen und der Einhaltung des Protokolls.

Kontextkosten

~830Tokens (Tool-Definitionen)
~856 BTypische Antwortgröße
Mittlere Auswirkung auf die Aufmerksamkeit (0.65% von 128k Kontext)

Dies ist die ungefähre Anzahl der Tokens, die jedes Mal verbraucht werden, wenn die Tools des Servers in den Kontext eines Modells geladen werden. Höhere Werte verringern die Aufmerksamkeit, die für andere Aufgaben verfügbar ist.

Installieren

Installation mit einem Klick

Fügen Sie dies Ihrer Datei `claude_desktop_config.json` hinzu:

{
  "mcpServers": {
    "mcp": {
      "url": "https://aitrainingdatabroker.com/api/mcp"
    }
  }
}

Remote-Endpunkte

https://aitrainingdatabroker.com/api/mcpstreamable-http

Was es kann

Tool-Inventar

Tools (5)

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🟢latest_posts(audience, limit)

The newest articles on the AI Training Data Broker blog, optionally only those for sellers (companies selling or licensing their data to AI labs) or buyers (labs sourcing licensed training data). Each result is a title, date, reading time, one-line summary and a link to the full article. Limitation: at most 10 per call, newest first.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "audience": {
      "type": "string",
      "enum": [
        "seller",
        "buyer",
        "deid"
      ],
      "description": "seller: companies selling or licensing their data. buyer: AI labs and model teams sourcing data. deid: de-identifying data to meet privacy laws (HIPAA, CCPA, GDPR). Leave out for all."
    },
    "limit": {
      "type": "integer",
      "description": "How many to return",
      "minimum": 1,
      "maximum": 10,
      "default": 8
    }
  },
  "required": [],
  "additionalProperties": false
}
🟢search_posts(query, audience, limit)

Search the AI Training Data Broker blog by topic, for example "what is my company data worth", "is it legal", "exclusive license", "RL data". Returns matching articles with a one-line summary and a link to the full article. Limitation: plain word matching in English, at most 10 results.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Words to search for"
    },
    "audience": {
      "type": "string",
      "enum": [
        "seller",
        "buyer",
        "deid"
      ],
      "description": "seller: companies selling or licensing their data. buyer: AI labs and model teams sourcing data. deid: de-identifying data to meet privacy laws (HIPAA, CCPA, GDPR). Leave out for all."
    },
    "limit": {
      "type": "integer",
      "description": "How many to return",
      "minimum": 1,
      "maximum": 10,
      "default": 8
    }
  },
  "required": [
    "query"
  ],
  "additionalProperties": false
}
🟢get_post(slug)

One article by slug (the last part of its URL) or its full URL: title, date, who it is for, the opening 120 words, the questions its FAQ answers, and a link to read the rest. Use it after a list or search result when the user wants to know what an article says. Limitation: returns the opening, not the full text; the full article and its answers are on the linked page.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "slug": {
      "type": "string",
      "description": "Article slug, e.g. how-much-do-ai-labs-pay-for-company-data, or the full URL"
    }
  },
  "required": [
    "slug"
  ],
  "additionalProperties": false
}
🟢search(query)

Connector-style search over the blog. Returns ids for fetch. Prefer search_posts for a filtered list.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Words to search for"
    }
  },
  "required": [
    "query"
  ],
  "additionalProperties": false
}
🟢fetch(id)

Connector-style fetch of one article by the id from search. Same opening as get_post.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "description": "Article slug from search"
    }
  },
  "required": [
    "id"
  ],
  "additionalProperties": false
}

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