An MCP server with a single evaluate_decision tool that returns noul, choice or score probabilities over a diff, log or plan, with output tokens set to zero on every call.
User repository on GitHub
open-sourced jev-flash-router: an MCP server for TypeSafe's new Jev model. AI coding agents waste hundreds of reasoning tokens just deciding which file to edit, which route to pick, or whether a diff breaks tests. Jev evaluates state and outputs calibrated probabilities. Works with Cursor, Windsurf, & Claude Code
Repo stats from the GitHub API, cached Oct 2026.
Zero-token-output decision router MCP server powered by TypeSafe Jev. AI coding agents waste hundreds of reasoning tokens just deciding which file to edit, which route to pick, or whether a diff breaks tests. jev-flash-router evaluates context, code diffs, logs, or planning options and returns calibrated probabilities in 150ms — with $0.00 output token cost. 150ms decisions — Lightning-fast evaluation via OpenRouter Decisions API. Zero output token cost — outputtokens: 0 on every call.
Quoted from the project's README. Read the full README.
Watch out
The headline latency figure comes with no method attached: the README states about 150ms without naming a percentile, a machine, or a benchmark script, so treat it as an unverified claim. Zero output tokens is the real trade-off, since you get probabilities and no explanation of why, because nothing is generated. Access goes through OpenRouter with the model named as typesafe/jev-latest, so you need an OpenRouter key with access to it rather than a TypeSafe key, which puts a third party in the path. The mapping from type to the shape of criteria is shown only by example, with no schema, and the README documents no validation, retry or timeout behavior if the returned probabilities are malformed. The install-skill command writes into your agent configuration files, so read what it changes. Copy reviewed against the repository README on 2026-10-04, not from running it.
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