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OverviewLive surfaces, product boundaries, and what is not sold yet.API DocsToken, wallet, deployer, and decision endpoints for builders.MCP ServerConnect RugBurn intelligence to local agent clients.RugBurn exposes Solana token, wallet, deployer, and decision evidence through the dashboard, API, Telegram workflow, and local MCP server.
Authentication, quotas, errors, token risk, wallet risk, deployer history, and decision endpoints.
Run RugBurn as a local tool server for agent clients.
Generate API keys and connect backend or agent clients safely.
Bring a workflow, token list, or pilot ask. We will test it against the live product.
Generate a key, call token risk, then inspect evidence, facets, hard caps, and limitations before your system takes action.
curl https://rugburn.io/api/v1/token/risk \ -H "Authorization: Bearer $RUGBURN_API_KEY" \ -H "Content-Type: application/json" \ -d '{"address":"TOKEN_MINT_ADDRESS"}'async function getTokenRisk(address: string) { const response = await fetch("https://rugburn.io/api/v1/token/risk", { method: "POST", headers: { "Authorization": `Bearer ${process.env.RUGBURN_API_KEY}`, "Content-Type": "application/json", }, body: JSON.stringify({ address }), }); if (!response.ok) throw new Error("RugBurn risk check failed"); return response.json();}import osimport requestsresponse = requests.post( "https://rugburn.io/api/v1/token/risk", headers={"Authorization": f"Bearer {os.environ['RUGBURN_API_KEY']}"}, json={"address": "TOKEN_MINT_ADDRESS"}, timeout=20,)response.raise_for_status()print(response.json()["data"]["recommendedAction"])Hackathon teams, agent builders, and bot developers
Call pre-trade checks and token evidence before an agent recommends, trades, alerts, or writes a public claim.
The API returns decision, confidence, evidence age, invalidation rules, sources, and limitations.
Fast Solana traders and Telegram groups
Paste a mint, read structure, liquidity, ownership, deployer, flow, and stale evidence before entry.
Use the app for quick triage, then add serious mints to watches for state-change alerts.
Private desks, quant groups, and paid communities
Add RugBurn as a pre-trade filter or post-signal review step before a strategy acts.
Batch candidate tokens offline, compare misses, and tune thresholds with weekly calibration notes.
Compliance teams and Solana payment operators
Screen token, wallet, and deployer evidence before routing suspicious assets for operator review.
Use wallet risk, deployer history, and token forensics as screening data, not a legal compliance guarantee.
Token teams, launchpads, and community operators
Share a clear risk report that explains where the project is strong and where buyers should still review.
A packet with facets, actors, freshness, and limitations is easier to defend than a naked score screenshot.
Use a low-scope test key. The key is not stored by this page, but production apps should call RugBurn from a backend or agent runtime.
RugBurn is forensic risk evidence and screening, not financial advice.
The API serves cached public v1 reports; unbounded full scans are protected.
The v3.3 behavioral model is a measured shadow model until calibration proves failure capture.
Accuracy alone is not marketed as rug detection when precision and recall are weak.
Read score index, risk level, facets, hard caps, sources, limitations, and generated metadata.
Treat precision, recall, failed-token separation, and Brier score as stronger model-health signals than accuracy alone.
Bring 20 token mints, one target workflow, and one success metric. RugBurn will help test fit quickly.
Send a token list, agent flow, trading rule, or forensic review case. We will tell you where RugBurn helps, where it misses, and what data is needed next.