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jev-gate-mcp

MCP gateway that trims noisy tool output and offers task classification and review advice, splitting work between local Laya and Jev.

MCP serverprototype

Overview

Jev Gate (MCP) helps AI coding assistants read less noise. It judges which parts of logs, search results and tool output are relevant to the current work and trims the rest in supported environments, shortens tool records while keeping kept content verbatim, and offers task classification and review suggestions for Claude Code and Codex. The README warns its opinions can be wrong and must not be treated as authorisation; completion checks still need real execution evidence.

With JEV_PROVIDER=laya, a local Laya model (about 540 MB, 1.2 to 1.9 GB memory when loaded) handles short fixed-type classifications such as task type, while Jev handles difficulty, risk, completion verification and fallback when Laya fails. Log trimming and compaction always use Jev. Laya is described as suitable only for limited trials, and savings are not yet measured. Local classifications are retained for review unless logging is turned off. Documentation is in Traditional Chinese.

What the decision model decides

TypeQuestionAnswers
Yes / noIs this section of tool output relevant to the current task?(inferred)—
ChoiceWhat type of task is this?(inferred)—
ScoreHow difficult or risky is this task?(inferred)—

How it works

  1. Tool output or a task arrives at the MCP gateway
  2. Laya tries simple classifications locally if enabled
  3. Jev handles relevance trimming, risk, difficulty and fallbacks
  4. Return trimmed output or advice to the assistant

Strengths

  • Less irrelevant text in context
  • Local model can save some cloud calls
  • Kept content stays verbatim

Caveats

  • Laya quality limited and under trial
  • Savings not yet measured
  • Local logs retain text by default

Getting started

`git clone https://github.com/royalskynet/jev-gate-mcp.git && cd jev-gate-mcp && npm install`, then follow the Claude Code or Codex connection guide.

At a glance

Type
MCP server
Status
prototype
Language
TypeScript
Runtime
MCP server (Node 22/24) with optional local Laya
Has code
yes

Use cases and integrations

How curated lists describe it

Frequently asked questions

What does it decide?

Which tool output is relevant, plus task type, difficulty and risk.

How do Laya and Jev split work?

Laya does short fixed classifications locally; Jev handles everything else and fallbacks.

Can its advice authorise actions?

No, the README says it can be wrong and is not authorisation.

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