Build with Tether USDT blacklist data
Three surfaces, all free, all public. Use whichever fits the stack: a REST API for traditional integrations, a Model Context Protocol server so any LLM client can call our data directly, and a HuggingFace dataset for retrieval / training.
Drop into Claude Desktop / Cursor / Continue
18 tools + 4 resources + 3 guided prompts. The AI client talks straight to our API — no HTTP glue, no API key.
npx -y cryptoalert-report-mcpClaude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"cryptoalert-report": {
"command": "npx",
"args": ["-y", "cryptoalert-report-mcp"]
}
}
}Try in chat after restart: “Investigate address 0x... — use cryptoalert-report-mcp.”
api.cryptoalert.report
No key required. 60 GET requests / minute per IP. CSV exports at 5 / minute. Anonymous tier sees preban events with a 24-hour delay; premium realtime via the Telegram bot.
curl https://api.cryptoalert.report/api/v1/stats/overview
curl 'https://api.cryptoalert.report/api/v1/events?type=ban&chain=eth&limit=10'
curl https://api.cryptoalert.report/api/v1/signers- Swagger UI: api.cryptoalert.report/api/docs
- ReDoc: api.cryptoalert.report/api/redoc
- OpenAPI: openapi.json
cryptoalert/usdt-blacklist-archive
Three Parquet files: ~24.5k events, ~10.4k addresses, ~26.5k multisig actions. License CC-BY-4.0. Re-generated periodically. Use for RAG, finetuning, or analysis.
import pandas as pd
events = pd.read_parquet("hf://datasets/cryptoalert/usdt-blacklist-archive/events.parquet")
print(events.groupby(["chain", "type"]).size())llms-full.txt
Always-fresh canonical reference at cryptoalert.report/llms-full.txt following the llmstxt.org convention. Pulls live totals on every request, 1h cache. Designed for crawlers used by ChatGPT, Claude, Perplexity, Gemini and similar AI search tools.
Free to cite and redistribute. Prefer cryptoalert.report (lowercase, no www). Issues / requests: [email protected] · @cryptoalert_supportbot