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decide-mcp

dakdevs/decide-mcp

Local MCP server delegating decisions to configurable models with percentage scores.

Agent Decisions77%Runner-up: Classification & Routing

What it is

A local stdio MCP server for agents that need a decision made. Send a decision, context, and 2–64 choices; receive a recommended choice with percentages. Defaults to TypeSafe AI Jev via AI Gateway.

How it uses Jev

Jev is the default evaluation model (typesafe-ai/jev). The server sends the decision, context, and choices through AI SDK 7's experimental_evaluate; Jev returns choice probabilities, which are multiplied by 100 as provider-distribution percentages. The agent then decides what to do next.

Primitives:choice

Technique worth stealing

Two-stage decision tree: a router selects a bias profile by description, then evaluation runs under that policy; explicit per-profile tools bypass routing.

Try it

npx -y decide-mcp@0.1.0 with AI_GATEWAY_API_KEY set in the MCP client env.

View on GitHub

judged by Jevjev-1.13.0

Evidence

Each line is one question put to Jev about the README. ≥ 0.60 reads as yes, ≤ 0.40 as no; in between Jev is not making a call.

  • Jev-centricyes0.66
  • Shows a System One patternunclear0.53
  • Handles uncertaintyno0.06
  • Measuredno0.05
  • Runnableyes0.98
  • Worth recommendingno0.30
  • Model replicano0.05
  • Problem scopescore on a 0–2 scale1.37
  • About Jevyes0.97

Signals by Jev jev-1.13.0, card written by DeepSeek V4.1 Flash from the README on 20 Sept 2026.