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jev-flash-router

An MCP server so coding agents stop spending tokens on small choices.

Ravinder82/jev-flash-routerREADME ↗
# jev-flash-router


[](https://www.npmjs.com/package/jev-flash-router)
[](https://github.com/Ravinder82/jev-flash-router/blob/main/LICENSE)
[](https://nodejs.org/)
[](https://modelcontextprotocol.io/)
[](https://openrouter.ai/)

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**.

---

## Features

- **~150ms decisions** — Lightning-fast evaluation via OpenRouter Decisions API
- **Zero output token cost** — `output_tokens: 0` on every call
- **TypeSafe Jev** — Powered by the cutting-edge `typesafe/jev-latest` model
- **MCP-native** — Works seamlessly with Cursor, Windsurf, Claude Desktop, and Claude Code
- **Zero-config** — Run via `npx` or build locally from source
- **Three decision formats** — `noul` (binary), `choice` (categorical), `score` (rubric)

---

## Quick Start

### 1. Get an OpenRouter API Key
Obtain an API key from [OpenRouter](https://openrouter.ai/) with access to the Jev model.

### 2. Client Setup

#### Option A: Run directly via npx (Recommended)
```json
{
  "mcpServers": {
    "jev": {
      "command": "npx",
      "args": ["-y", "jev-flash-router"],
      "env": {
        "OPENROUTER_API_KEY": "sk-or-v1-YOUR-ACTUAL-API-KEY"
      }
    }
  }
}

```

#### Option B: Run from Local Source (Cloned Repository)

```json
{
  "mcpServers": {
    "jev": {
      "command": "node",
      "args": ["/path/to/jev-flash-router/dist/index.js"],
      "env": {
        "OPENROUTER_API_KEY": "sk-or-v1-YOUR-ACTUAL-API-KEY"
      }
    }
  }
}

```

### 3

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