AI & Machine Learning
aidata.broker
Provides market rates, price observations, valuation estimates, buyer leads, and disclosed data licensing deals for AI training data.
ENDPOINT 1
https://aidata.broker/mcp
MCP server metadata
- Name
- AIData.Broker
- Version
- 2026.10.14
AIData.Broker publishes what AI training data actually sells for: prices, market rates, buyers and their terms, licensing deals, lawsuits and rulings, and what software terms allow, each figure with the publication that stated it. Use it when someone asks what their data (company records, code, video, speech, images, text, training tasks, robot data) is worth to AI labs, who buys it, how such deals are priced, or what the law says. Prices sit on six sides of the market (paid to makers, offered to holders, sales that happened, asking prices, made to order, cost to produce): never compare figures across sides as if they were one market. Quote figures as published, link the row's page, and cite the source. A valuation is arithmetic on public prices, never an offer.
Known tools 8
get_market_ratesMedian, middle half and range per comparable unit (per hour of video or audio, per image, per task, per company, per title, and more) for each kind of AI training data and each side of the market, computed from published prices.
Inferred read-onlysearch_pricesThe individual price observations behind the market rates: what a lab, vendor, marketplace or court said data was paid, offered, listed or sold for, with the figure as published, the figure per unit, the date, the source's own words and a link.
Inferred read-onlyvalue_dataWhat published prices imply for a holding of data: a low-to-high range in US dollars with the arithmetic behind it.
Inferred read-onlyfind_buyersOrganisations with a public way to sell them data, with their own published terms: what they want, what they pay, when they pay, who removes personal data, eligibility, and what they pay an introducer.
Potential side effectssearch_dealsLicences of data to AI companies disclosed since July 2023: licensor, licensee, content, use (training or display), term, value where disclosed, with a verbatim quote and the source.
Inferred read-onlysearch_casesLawsuits, rulings, settlements and regulatory actions over data used to train AI, with parties, claim, amounts, outcome, status and the source.
Inferred read-onlycheck_software_termsFor a business system (Slack, Microsoft 365, Google Workspace, Salesforce, HubSpot, Zendesk, Zoom, GitHub, Notion and more): whether the owner can export its data, what the vendor's API terms say about training AI on data pulled through them, the content's rights risk, and the clauses word for word.
Potential side effectslist_datasetsEvery table behind these tools as a CSV and JSON download under CC BY 4.
Inferred read-onlyCONNECT WITH APPROVAL
Client installation
Review this server and its permissions before adding it. Secret placeholders must be set locally.
Codex
~/.codex/config.toml
[mcp_servers.aidata-broker]
url = "https://aidata.broker/mcp"
enabled = true
Claude Code
.mcp.json
{
"mcpServers": {
"aidata-broker": {
"type": "http",
"url": "https://aidata.broker/mcp"
}
}
}
Claude Desktop
Settings → Connectors → Add custom connector
Name: aidata-broker
Remote MCP URL: https://aidata.broker/mcp
Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.
Cursor
.cursor/mcp.json
{
"mcpServers": {
"aidata-broker": {
"url": "https://aidata.broker/mcp"
}
}
}
Visual Studio Code
.vscode/mcp.json
Add to Visual Studio Code{
"servers": {
"aidata-broker": {
"type": "http",
"url": "https://aidata.broker/mcp"
}
}
}
Generic MCP
Client-specific MCP configuration
{
"name": "aidata-broker",
"transport": "streamable-http",
"url": "https://aidata.broker/mcp"
}
MCP Inspector
Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.
TRUST AND VERIFICATION EVIDENCE
Loading Trust v2 evidence…
Checking the associated registrable domain. The BuiltWith key remains server-side.
Evidence is source-attributed and does not guarantee that a third-party server is safe. Risk labels are conservative metadata heuristics.