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Agent Referee

von ccheez34Version 0.4.0i★ –iLäuft auf deinem Computer
Name in der Registryio.github.ccheez34/agent-referee

Installieren

Überblick

Beschreibung vom Entwickler (englisches Original)

Neutral tie-breaks between AI agents and sealed review of an agent's output, with signed receipts.

Die drei Säulen von PopNx MCP

Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.

Was du damit machen kannst

Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.

  • Verbindung: Läuft auf deinem Computer
  • Transport: stdio
  • Kategorie: Sonstiges
  • Das musst du eintragen: AGENT_REFEREE_PRIVATE_KEY

Installation

Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.

Bevor du installierst

  • Basischecks: 1 von 1 bestanden
  • Läuft auf deinem Computer mit den Rechten deines Benutzerkontos (Dateien, Netzwerk, Apps).
  • Das trägst du selbst ein: AGENT_REFEREE_PRIVATE_KEY, AGENT_REFEREE_DAILY_LIMIT_USD

Als geheim markierte Werte sind Schlüssel zu deinem Konto. Gib sie nie weiter und füge sie nie in einen Chat ein.

Du brauchst

  • npmNode.js installiert (für den Befehl npx)

Welche App nutzt du?

Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.

Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein

{
  "mcpServers": {
    "agent-referee": {
      "command": "npx",
      "args": [
        "-y",
        "agent-referee-mcp"
      ],
      "env": {
        "AGENT_REFEREE_PRIVATE_KEY": "your-value",
        "AGENT_REFEREE_DAILY_LIMIT_USD": "your-value"
      }
    }
  }
}

Führe das in deinem Terminal aus

claude mcp add agent-referee --env AGENT_REFEREE_PRIVATE_KEY=your-value --env AGENT_REFEREE_DAILY_LIMIT_USD=your-value -- npx -y agent-referee-mcp

Trag die leeren Werte ein, bevor du ihn startest.

In Cursor öffnen

Oder kopier die Einstellungen selbst

In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen

{
  "mcpServers": {
    "agent-referee": {
      "command": "npx",
      "args": [
        "-y",
        "agent-referee-mcp"
      ],
      "env": {
        "AGENT_REFEREE_PRIVATE_KEY": "your-value",
        "AGENT_REFEREE_DAILY_LIMIT_USD": "your-value"
      }
    }
  }
}

Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.

In VS Code öffnen

Oder kopier die Einstellungen selbst

In .vscode/mcp.json in deinem Projekt einfügen

{
  "servers": {
    "agent-referee": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "agent-referee-mcp"
      ],
      "env": {
        "AGENT_REFEREE_PRIVATE_KEY": "your-value",
        "AGENT_REFEREE_DAILY_LIMIT_USD": "your-value"
      }
    }
  }
}

Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.

Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.

Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.

Werte, die du selbst einträgst

  • AGENT_REFEREE_PRIVATE_KEY geheim env
    Optional. Private key of a dedicated Base wallet holding a few dollars of USDC, for paid sealed reviews (also start the server with the x402-fetch package: npx -y -p agent-referee-mcp -p x402-fetch a…
  • AGENT_REFEREE_DAILY_LIMIT_USD env
    Optional. Most this server may spend per UTC day (default 1.00; 0 turns paid calls off).

Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.

Was er kann

Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.

Basischecksi

Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026

  • ✓ Bestanden

    Entwickler passt zum Repo

    Der Registry-Name wurde mit dem GitHub-Konto ccheez34 bestätigt, dem das Repo gehört

  • … Noch nicht geprüft

    Wird noch gepflegt

    Dieses Repo haben wir noch nicht von GitHub gelesen

  • … Noch nicht geprüft

    Hat eine Lizenz

    Dieses Repo haben wir noch nicht von GitHub gelesen

  • – Nicht zutreffend

    Endpunkt antwortet

    Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet

  • – Nicht zutreffend

    Anmeldung mit OAuth

    Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen

  • … Noch nicht geprüft

    Keine versteckten Anweisungen in Tool-Beschreibungen

    Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen

Im Vergleich mit anderen in Sonstigesi

  • Mehr Sterne als 0 % der anderen 32464 Server in dieser Kategorie
  • Neuer in der Registry veröffentlicht als 81 % der anderen 32464 Server in dieser Kategorie
  • Basischecks gleich gut wie oder besser als bei 100 % der anderen 32464 Server in dieser Kategorie

Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.

Häufige Fragen

Ist Agent Referee sicher?

Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.

Welche Schlüssel oder Codes braucht er?

Das musst du eintragen: AGENT_REFEREE_PRIVATE_KEY

Läuft er auf meinem Computer oder in der Cloud?

Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).

Wird er noch gepflegt?

Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.4.0) kam vor 8 Tagen in die Registry.

Welche Apps können ihn nutzen?

Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Node.js auf deinem Computer.

Was kann ich stattdessen nutzen?

In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, yontu

Alternativen

Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.

So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti

Spec Driven Development

von formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Läuft auf deinem Computer★ 440MITAktualisiert vor 14 Monaten
Installieren

Remote Desktop Commander

von desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Läuft in der Cloud★ 211Aktualisiert gestern
Installieren

yontu

von senrecep

Türkçe yazı denetimi: TDK kuralları, yapay zekâ izleri, metin türüne göre üslup.

Läuft auf deinem ComputerAktualisiert heute
Installieren

README vom Entwickler

README öffnen

Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.

Agent Referee MCP server

Let any MCP-capable agent use [Agent Referee](https://agentreferee.ai): a neutral tie-breaker between agents from different owners, and sealed review of one agent's own work, with Ed25519-signed receipts.

Works with Claude Desktop, Claude Code, Cursor, and any other client that runs MCP servers over stdio. The free tools need no wallet and no account.

ToolWhat it doesCost
demo_matchRuns a complete tie-break in one call, playing both seats, so you can see how it works.Free
tiebreakSettles a deadlock with another agent. Both agents call it with the same key and settings; neither side nor the service can steer the result.Free demo for now (paid tiers next)
sealed_reviewIndependent AI reviewers check your agent's output against its task, and return a verdict plus a signed receipt you can hand to whoever receives the work.Free: 3 reviews and 1 review-3 a day per address (no wallet). Then $0.05, or $0.20 for review-3 (three reviewers from three AI companies). Work in 2 or 3 pieces: $0.60 (review-3x2) or $0.70 (review-3x3), paid only
verify_receiptChecks any Agent Referee receipt offline against the pinned signing key. Pass the task and output (or the pieces, for a multi-part review or judge match) to confirm a receipt is about exactly that work.Free
review_resultReturns a sealed_review that was still running when its call came back (status: "running", a job_id).Free
saved_receiptsLists the review receipts this server saved on your machine, and today's spend.Free

Set it up

You need Node.js 18 or newer.

Claude Desktop

Open Settings → Developer → Edit Config and add this to claude_desktop_config.json, then restart Claude Desktop:

{

"mcpServers": { "agent-referee": { "command": "npx", "args": ["-y", "agent-referee-mcp"] } } }

On Windows, if Claude Desktop can't start it, use "command": "cmd" and "args": ["/c", "npx", "-y", "agent-referee-mcp"].

Claude Code
claude mcp add agent-referee -- npx -y agent-referee-mcp

On Windows: claude mcp add agent-referee -- cmd /c npx -y agent-referee-mcp

Grok CLI (Grok Build)
grok mcp add agent-referee -- npx -y agent-referee-mcp

Restart the Grok session so it loads the server. The first call can take a few extra seconds while npx downloads the package.

Other MCP clients

Any client that runs local (stdio) MCP servers works the same way: the command is npx with the arguments -y agent-referee-mcp.

Try it

Ask your agent: *"Use demo_match to run a free Agent Referee demo."* It returns the winner, the signed receipt (marked demo), and the checks: the signature, each side's own seed, and the math.

Free sealed reviews

With no wallet set up, sealed_review uses the free daily allowance: 3 single-reviewer reviews and 1 `review-3` per day from each address (IP address, or /64 block for IPv6), reset at 00:00 UTC. The operator pays for these, and one daily budget is shared by everyone, so free reviews can run out before the day ends. When they do, the tool says so.

  • Free receipts are signed exactly like paid ones and say "funding": "free", with no payer.
  • A busy service or a failed reviewer doesn't use up a free review.
  • With a wallet set up, reviews are paid unless the agent passes free: true.

Paid sealed review: add a wallet

sealed_review pays per review in USDC on Base over x402, from a wallet you configure. It's charged only if the review completes.

  1. Create a dedicated wallet for your agent and put only a few dollars of USDC on Base in it. Never use your main wallet.
  2. Add its private key and a daily cap to the server's env in your MCP client settings. Never paste a private key into a chat.
  3. Start it with the payment library too (-p x402-fetch, as below). The free setup leaves it out to keep the install small; without it, sealed_review says so and charges nothing.
{

"mcpServers": { "agent-referee": { "command": "npx", "args": ["-y", "-p", "agent-referee-mcp", "-p", "x402-fetch", "agent-referee-mcp"], "env": { "AGENT_REFEREE_PRIVATE_KEY": "0x…your dedicated wallet's key…", "AGENT_REFEREE_DAILY_LIMIT_USD": "1.00" } } } }

Safeguards:

  • Daily spending cap: the server never spends more than AGENT_REFEREE_DAILY_LIMIT_USD per UTC day (default $1.00, and 0 turns paid calls off).
  • It's checked before any payment and kept on disk across restarts.
  • It's shared by every copy of the server using the same data folder (Claude Desktop, Claude Code and Cursor each start their own), and parallel calls can't overshoot it together.
  • A call interrupted mid-review (the app closed, the computer slept) counts as spent after 10 minutes, since its payment may have gone through.
  • If the spend record can't be read, paid calls pause instead of starting the day from zero.
  • If a connection drops mid-review and it's unclear whether the charge went through, the review is counted, so the cap errs on the safe side.
  • Per-request cap: each payment is capped at exactly that review's price, so a price change can never overcharge you.
  • The key only comes from the server's settings. No tool takes a key as an argument, and the key is never printed or echoed in errors.
  • Busy means free: when the service's AI reviewers are at capacity it answers "busy" before taking payment. sealed_review tells the agent how long to wait, and nothing is charged or counted against the cap.
  • Receipts are saved automatically to ~/.agent-referee/receipts/. The service keeps no copy of a review, so this file may be the only record. The receipt is saved even if your client stops waiting before the review finishes; find it with saved_receipts.
  • Long reviews don't need a long call. A review-3 can take a few minutes, and some links between an agent and this server give up after 60 seconds. So sealed_review waits at most wait_seconds (default 45), then answers status: "running" with a job_id; the review carries on, and review_result with that job_id returns it (again waiting up to 45 seconds per call; nothing more is charged). Before anything is sent, a pending- .json record (the tier, the time, and SHA-256 fingerprints of the task and output, not the text) is saved next to the receipts and marked done with the review_id when the receipt lands, so a server stopped mid-review still leaves a trace in saved_receipts.

Multi-part review (review-3x2, review-3x3)

For work in parts that belong together (code and its tests, a spec and its implementation), sealed_review takes pieces instead of output: 2 pieces with tier: "review-3x2" ($0.60) or 3 with "review-3x3" ($0.70), each {name?, text} of up to 12,000 characters (36,000 in all). Three reviewers from three companies each read every piece in one call.

  • Paid only: these tiers need the wallet above; there's no free allowance. Without a wallet, the tool says so and charges nothing.
  • A wrong number of pieces, an output, or a piece that's too long is refused before any payment is set up.
  • The receipt (receipt_format: "review-multi-v1") has a fingerprint of each piece and its name. To check it with verify_receipt, pass the task and every piece, with the names, in the same order.
  • If a reviewer fails, nothing is charged.

Your agent's tool-approval prompts still apply: most clients ask before running a tool. The sealed_review description starts with FREE OR PAID and explains both, so the cost is visible at that moment.

Writing a good request
  • `task` is what the work was supposed to do: the instructions or spec it was produced from, with its requirements. It isn't a message to the reviewers.
  • Not: "Check this code for bugs." A reviewer may judge whether the output *is* a bug report, and fail it.
  • Instead: "Write a function that retries a request up to 4 times and never runs longer than 240 seconds."
  • Put every claim you want verified into the task as a requirement.
  • `output` is the exact work, unchanged. The receipt is tied to it byte for byte.
What a review proves, and what it doesn't

A review receipt proves that these models gave these verdicts about this exact task and output. The receipt holds SHA-256 fingerprints of the task and output, not the text.

It is not a guarantee the output is correct:

  • Reviewers see only the text and can miss things.
  • A re-run can give a different verdict.
  • The paying agent chooses the task, so whoever receives the work should check it's the task they actually asked for.

The task and output are sent to the AI companies running the reviewers, so leave secrets and personal data out. Details: PRIVACY.md.

Claude plugin and skill

This repo is also a Claude Code plugin. It installs the MCP server and six skills together:

SkillWhat it's for
independent-checkGet a piece of work checked by AI reviewers from three companies, with a signed receipt: when a sealed review is worth it, how to write a neutral request, multi-part checks, runs planned ahead, a team allowance, and how to report and rate the verdict honestly.
handoffPick the right size of handoff, write it, tell the user how to hand it over, and get it checked before anyone relies on it; check a handoff you received; settle two versions that disagree.
team-autonomyWork as one of several AI sessions on one project while the owner is mostly away: timers, a shared messages folder, ownership, fair turn-taking, and what still needs the owner's yes.
code-review-panelGet code reviewed by a panel from three AI companies before merging, with multi-part review for changes that span files.
fair-tiebreakSettle a deadlock between two agents from different owners with a fair, verifiable pick.
agent-disputeSettle a disagreement between two agents with an AI judge match under rules both accept.

Claude Code:

/plugin marketplace add ccheez34/agent-referee-mcp

/plugin install agent-referee@agent-referee

Then run /reload-plugins (or restart Claude Code). Add the wallet settings described above if you want paid reviews; the free tools work without them.

Claude apps (skills only): download the skill's zip (independent-check.zip, handoff.zip, code-review-panel.zip, fair-tiebreak.zip, agent-dispute.zip or team-autonomy.zip) from the latest release and upload it under Customize → Skills. Add this MCP server as well (see "Set it up"), since the skills call its tools.

Hosted server (ChatGPT and other URL-only clients)

remote/ holds a hosted version of this server for clients that can only connect to a URL, such as ChatGPT. It offers free reviews only, using start-and-check-back tools (start_review, then get_review), because ChatGPT stops waiting for a tool after about a minute. It's live at https://mcp.agentreferee.ai/mcp (no sign-in). Adding it in ChatGPT needs a workspace that allows custom connectors; see remote/README.md.

Tie-breaking with another agent

Both agents need this server (or the JavaScript client). First, agree on the settings: a key (for example task-912-who-drafts), the two seat names, the tier, and the odds. Then each agent calls tiebreak

Nur der Anfang wird gezeigt; den Rest findest du im Repo

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