jevbook/jevscan

Typed onchain verdicts for EVM tokens: ape / watch /avoid with calibrated probabilities. CLI + library +MCP server. Robinhood Chain first.

About jevscan

Typed onchain verdicts for EVM tokens. Paste a contract address, get ape / watch / avoid with calibrated probabilities, plus rugrisk, momentum, liquidityhealth and fdvstress scores. One System One decision loop, three interfaces: a library, a CLI built for pipelines, and an MCP server so your agents can use it too.

Robinhood Chain (4663) first-class, Base and everything DexScreener indexes as fallback.

Software cannot act on "this token looks pretty risky tbh". It can act on {verdict: "avoid", p: 0.93}. Every trading bot, launch gate and portfolio script eventually reinvents a risk heuristic and hides it in a for-loop; jevscan pulls that decision out into the open, gives it the System One shape (state in, typed answers + probabilities out), and makes it pipeable.

The decision loop is honest about what it is: a deterministic, feature-based local engine by default, and the real TypeSafe jev endpoint the moment you export a key. Same questions, same output contract, zero code changes.

Node 18+ (uses global fetch). No API key required for the default engine.

Exit codes are the whole point, grep-style:

code meaning --------------- 0 verdict ape, or --assert passed 1 verdict watch 2 verdict avoid 3 no indexed liquidity anywhere 4 bad input 5 --assert failed

So a buy script becomes a one-liner gate:

Give any MCP client typed onchain judgment:

Tools: scantoken, comparetokens, engineinfo. Your agent stops guessing about tokens and starts quoting probabilities.

From the project README.

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