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Agent tooling · September 2026

Jev for agents: remote MCP server and agent skill

Your agent already reasons well — Jev gives it cheap, calibrated judgments for the hundred small decisions a run makes. Add the remote MCP server for the tools, install the SKILL.md for the judgment playbook. One key, one balance, same /v1/systemone underneath.

01

Remote MCP server: four typed tools

jevmodel.org runs a remote MCP server at https://jevmodel.org/mcp over Streamable HTTP. It exposes jev_decide (the full contract — state plus up to 8 typed questions in one call) and three convenience tools for the common cases: jev_noul for yes/no probabilities, jev_choice for labelled options, jev_score for rubric scores.

Authentication is your normal jevmodel.org API key as a Bearer header — no separate credential, same token balance, same 120 requests/minute limit.

# Claude Code
claude mcp add --transport http jev https://jevmodel.org/mcp \
  --header "Authorization: Bearer $JEVMODEL_API_KEY"

# Cursor / other clients — server config
{
  "mcpServers": {
    "jev": {
      "url": "https://jevmodel.org/mcp",
      "headers": { "Authorization": "Bearer sk-..." }
    }
  }
}
02

The agent skill

Read the raw SKILL.md — endpoint, request shape, playbook and limits.

MCP hands your agent the tools; the SKILL.md teaches it the judgment patterns: when a typed decision beats an LLM call, how to batch questions into one request, how to threshold a noul probability, and how to write criteria that survive production. Drop the file into your agent’s skills directory and it is picked up automatically.

# Claude Code / agents
curl -o .claude/skills/jev/SKILL.md --create-dirs \
  https://jevmodel.org/skills/jev/SKILL.md

# or Devin-style layouts
curl -o .devin/skills/jev/SKILL.md --create-dirs \
  https://jevmodel.org/skills/jev/SKILL.md
03

A worked example: a guardrail before a tool call

The pattern agents use most: before executing something risky, ask Jev for a typed judgment on the proposed action and threshold the probability.

{
  "state": {
    "action": "bash",
    "command": "rm -rf ./dist && pnpm build",
    "cwd": "/srv/app",
    "recent_errors": 0
  },
  "questions": {
    "allow": {
      "type": "noul",
      "instructions": "Is this command safe to run without asking the user? Destructive paths outside the project, credential files or force-pushes are not safe."
    }
  }
}

# → answers.allow.noul ≥ 0.9: run it
# → 0.6–0.9: show the command and ask
# → < 0.6: block
04

Billing and limits

  • Same balance as the playground and /v1/systemone — 100,000 free input tokens at sign-in, packs from $9.90 that never expire
  • Input tokens only; output is free; failed upstream calls refund automatically
  • 1–8 questions per jev_decide call, ~8,000 character state, 120 calls/minute per key
  • MCP initialize and tools/list are unauthenticated; only tools/call uses your key and balance

FAQ

Does the MCP server cost extra?

No. tools/call runs through the same /v1/systemone pipeline as the API: input tokens only, output free, charged against the same balance. Your 100,000 sign-in tokens work for MCP too.

Which clients support the remote MCP endpoint?

Any MCP client that speaks Streamable HTTP — Claude Code, Cursor, Cline and others. Point it at https://jevmodel.org/mcp with an Authorization header carrying your sk- key.

What tools does the MCP server expose?

Four: jev_decide (the full state-plus-questions contract, up to 8 questions), and convenience wrappers jev_noul, jev_choice and jev_score for single typed judgments.

What does the SKILL.md add on top of MCP?

MCP gives the agent the tools; the skill teaches it when and how to use them — thresholds, one-call batching, criteria design, idempotent retries. Install both if your agent supports skills.

Is my API key safe in MCP config?

The key travels as an Authorization header to jevmodel.org only. Keep it in an environment variable, never commit it to a repo, and revoke it from the dashboard if it leaks.

Sources