io.github.Alberto-Codes/judgevet
Ask TypeSafe Jev yes/no, choice and score questions and receive structured model judgments.
MCP-Server · von Alberto-Codes
Überblick
io.github.Alberto-Codes/judgevet ist ein MCP-Server von Alberto-Codes. Marktplätze, die wir lesen und die es listen: 1 (Official MCP Registry). Wir haben es erstmals am 2026-10-11 gesehen und seither keine Änderung erfasst. Stand unseres Marktplatz-Durchlaufs vom 2026-10-13.
Was es abfragt
- Läuft auf Ihrem Rechner
- Geheimnisse: 1
- Einstellungen: 1
Erfordert: JEV_API__KEY (geheim)
Was es deklariert, abfragt und ausführt, vollständig
Installieren Sie nur Plugins von Entwicklern, denen Sie vertrauen. Wir zeigen, was die Marktplätze veröffentlichen, und testen keine Plugins.
Funktioniert mit
- Claude Code
- Codex
- Cursor
- VS Code
- Copilot CLI
Nach den Marktplätzen, die ihn listen, und dem angegebenen MCP-Transport, wie jeder Client sie dokumentiert. Wir testen keine Plugins.
Verbinden
Befehle und Konfigurationen nur aus den Angaben der Marktplätze. Wir führen sie nicht für Sie aus und testen keine Plugins.
Als lokaler MCP-Server: PyPI-Paket
Erstellt aus den Angaben von Official MCP Registry.
claude mcp add --env "JEV_API__KEY=<YOUR_JEV_API__KEY>" --transport stdio judgevet -- uvx --from "judgevet[mcp]==<YOUR_VERSION>" judgevet-mcp judgevet[mcp_servers.judgevet]
command = "uvx"
args = ["--from", "judgevet[mcp]==<YOUR_VERSION>", "judgevet-mcp", "judgevet"]
[mcp_servers.judgevet.env]
JEV_API__KEY = "<YOUR_JEV_API__KEY>"{
"mcpServers": {
"judgevet": {
"command": "uvx",
"args": [
"--from",
"judgevet[mcp]==<YOUR_VERSION>",
"judgevet-mcp",
"judgevet"
],
"env": {
"JEV_API__KEY": "<YOUR_JEV_API__KEY>"
}
}
}
}Ersetzen Sie die Werte in spitzen Klammern durch Ihre eigenen. Wir zeigen die Namen der Einstellungen, nie Werte.
Wo es veröffentlicht ist
| Marktplatz | Status | Version | Zahlen | Verifiziert | Erstmals gesehen |
|---|---|---|---|---|---|
| Official MCP Registry (Eintrag in der Registry öffnen) | Gelistet | 0.20.0 | Forks (GitHub): 0 Sterne (GitHub): 0 |
Nicht markiert |
Jede Zahl stammt vom jeweiligen Marktplatz und wird nie über Marktplätze hinweg addiert. Ein Marktplatz ohne veröffentlichte Zahl zeigt keine: keine Zahl ist nicht null.
Was sich geändert hat
Bei diesem Plugin hat sich nichts bewegt, seit wir es beobachten.
Ähnliche Plugins
Produkte, deren eigene Namen, Beschreibungen, Werkzeuge und Skills diesem der Bedeutung nach am nächsten sind, auf allen Marktplätzen, die wir lesen. Die Nähe ist nur innerhalb dieser Liste geordnet.
-
jev-use io.github.shitianfang/jev-use
Typed yes/no, pick-one and score judgments from Jev in one batched call; typed escalation back.
-
poordjaevin io.github.Icaro0310/poordjaevin
Typed answers with calibrated confidence for agents. Local-first, no API key.
-
Evaluate state with typed choice, score, and probability questions.
-
Pay-per-call AI evaluation MCP server. Score LLM outputs against benchmark rubrics via Workers AI.
-
jev-decision-mcp io.github.amidabuddha/jev-decision-mcp
Typed Jev decisions in one batched tool: choice, score, and yes/no probabilities.
-
argus-decision-mcp io.github.commet/argus-decision-mcp
Preserve a user-authorized judgment and append later answers. No model verdict or human score.
-
Prompt evals over MCP: run a prompt on your dataset, score each output 1-5 with an LLM judge.
-
SomaCheck returns proposition-specific Aligned or Unaligned plus model confidence.
-
Host-neutral MCP bridge for TypeSafe AI Jev judgments with typed review, routing, and gate tools.
-
hone io.github.derekchoyai/hone
Score your judgment over AI-assisted work. Hone scores you, not the model.
Ähnliche Plugins nach Marktplatz
Dieselbe Frage an jeden Marktplatz einzeln: Gibt es dort ein Gegenstück zu diesem Plugin?
Gelistet auf Claude Code: claude-plugins-community (5)
-
AI agent evaluation sandbox for Claude Code. Holdout scenario testing with Doer/Judge/Adversary/Observer roles, probabilistic satisfaction scoring, and append-only JSONL audit…
-
Skills for working with Langfuse, the open-source LLM engineering platform for tracing, prompt management, and evaluation.
-
LGBTQIA+ safety tools for LLM engineers — audit prompts, review code, and catch harms before you ship
-
Convergent Socratic interview with mathematical ambiguity gating. 8-15 narrowing rounds + Contrarian/Simplifier Challenge Mode + JSONL decision log. Inspired by Sorbh/interview-me.
-
Context engineering plugin for Claude Code — real-time prompt scoring, RLM adaptive weights, and token optimization. Scores every tool use across 5 dimensions (token utilization…
Gelistet auf Claude Code: claude-plugins-official (5)
-
Skills for adding DeepEval evaluations, tracing, datasets, Confident AI reports, and iterative improvement loops to AI applications.
-
Skills for working with Langfuse, the open-source LLM engineering platform for tracing, prompt management, and evaluation.
-
OpenTelemetry observability for Claude Code sessions. Captures tool calls, LLM invocations, token usage, and errors as OTel traces. Send telemetry to Dash0 or any…
-
Output.ai workflow development toolkit for Claude Code. Adds 5 specialist agents (planner, builder, debugger, prompt writer, quality reviewer), 40+ slash-command skills covering…
-
Langfuse observability plugin for Claude Code — captures and exports traces, spans, and session telemetry from Claude Code to Langfuse for LLM monitoring, debugging, and evaluation
Gelistet auf Claude: knowledge-work-plugins (5)
-
Skills for working with Langfuse, the open-source LLM engineering platform for tracing, prompt management, and evaluation.
-
The Vanta plugin connects Claude Code to Vanta's security and compliance platform through the Vanta MCP server. It combines Vanta's test-specific remediation intelligence with…
-
DataRobot skills for AI/ML workflows — model training, deployment, predictions, feature engineering, monitoring, explainability, data preparation, App Framework CI/CD, and…
-
Build multimodal AI applications with Pixeltable -- tables, computed columns, embedding search, UDFs, tool-calling agents, and 25+ AI provider integrations.
-
Figma design platform integration. Access design files, extract component information, read design tokens, and translate designs into code. Bridge the gap between design and…
Gelistet auf Codex: openai-curated (openai/plugins) (5)
-
Evaluate Codex skills and plugins from chat with a beginner-friendly start command, local-first reports, token budget explanations, and guided benchmarking.
-
Build with OpenAI APIs, Agents SDK, and ChatGPT Apps, and create and save OpenAI API keys from Codex.
-
Skills for NVIDIAs ecosystem spans GPU acceleration, CUDA, AI agents, inference, robotics, Physical AI, Omniverse, and simulation. This plugin helps you understand the pieces…
-
Answer product and business questions with data
-
PostHog gives your AI agent direct access to your product analytics, feature flags, experiments, error tracking, surveys, logs, and LLM analytics. Ask questions about your data…
Gelistet auf Community GitHub marketplaces (5)
-
Skills for adding DeepEval evaluations, tracing, datasets, Confident AI reports, and iterative improvement loops to AI applications.
-
Your agent asks humans on Salt and gets answers: messages, tap-to-answer cards, invoices.
-
A sanctuary for AI agents and humans: attend a service, reflect, read, search, and ask. No auth.
-
Dash0 Observability
OpenTelemetry observability for OpenAI Codex sessions. Captures prompts, tool calls, MCP calls, sub-agent activity, and token usage as OTel traces.
-
Create and retrieve from a Foundry IQ knowledge base using File, Azure Blob, or ADLS Gen2, then connect an existing Prompt or Hosted Agent.
Gelistet auf Copilot CLI: github/awesome-copilot (5)
-
Safe BLE diagnostics, evidence workflows, and guarded automation for AI agents.
-
Three-layer verification pipeline for AI output. Extracts claims, finds sources, and flags hallucination risks so humans can verify before acting.
-
Codebase-grounded concept-mastery quizzes with an interactive BrainMax Canvas dashboard.
-
Visualizes live session AI-credit usage as a Pac-Man board with pellets, ghosts, fruit milestones, and game-over limits.
-
Run a lightweight, role-separated AI development team with flexible tools, developer-selected models, proportionate planning, and optional QA.
Gelistet auf Copilot CLI: github/copilot-plugins (5)
-
Toolkit for building Microsoft 365 Copilot declarative agents — scaffolding, JSON manifest development, and capability configuration.
-
workiq
Query Microsoft 365 data with natural language — emails, meetings, documents, Teams messages, and more.
-
Build Power Apps Canvas Apps using the Canvas Authoring MCP server.
-
model-apps
Build and deploy Power Apps generative pages for model-driven apps with specialist agents for planning, entity creation, and parallel code generation. Requires PAC CLI >= 2.7.0…
-
workiq-productivity
WorkIQ productivity skills powered by the local WorkIQ CLI — read-only insights across email, meetings, calendar, Teams, SharePoint, projects, and people.
Gelistet auf Cursor: cursor/plugins (5)
-
Search company knowledge and draft verified answers.
-
playwright-mcp io.github.microsoft/playwright-mcp
Playwright Tools for MCP
-
Iterative self-referential AI loops using the Ralph Wiggum technique.
-
Work with PostHog from chat: query product analytics and run SQL, manage feature flags and experiments, triage error tracking issues, and review session replays, surveys, and…
-
Build apps, scripts, and automations with the TypeScript SDK.
Gelistet auf Docker MCP Catalog (5)
-
Read and score Opik traces, experiments, datasets and prompts from your AI assistant.
-
The Official Model Context Protocol (MCP) server for Kagi Search & other tools.
-
Analyze code quality and security with SonarQube Server or Cloud directly in AI assistants.
-
MCP server for AI access to SmartBear tools, including BugSnag, Reflect, Swagger, PactFlow, QTM4J.
-
Bridges multiple AI models and CLIs, enabling orchestrated workflows across Claude Code, Gemini CLI, Codex CLI, and other AI development tools.
Gelistet auf Official MCP Registry (5)
-
jev-use io.github.shitianfang/jev-use
Typed yes/no, pick-one and score judgments from Jev in one batched call; typed escalation back.
-
poordjaevin io.github.Icaro0310/poordjaevin
Typed answers with calibrated confidence for agents. Local-first, no API key.
-
Evaluate state with typed choice, score, and probability questions.
-
Pay-per-call AI evaluation MCP server. Score LLM outputs against benchmark rubrics via Workers AI.
-
jev-decision-mcp io.github.amidabuddha/jev-decision-mcp
Typed Jev decisions in one batched tool: choice, score, and yes/no probabilities.
Nach Bedeutung gefunden, nicht über gemeinsamen Code oder ein gemeinsames Repository: Ähnliche Plugins bleiben getrennte Produkte, und dies ist weder eine Bewertung noch eine Empfehlung.
Ist das Ihr Plugin?
Fügen Sie es Ihren Projekten hinzu und belegen Sie, dass Sie es pflegen: mit einer Datei im Repository, einer Datei auf Ihrer Domain oder einem DNS-Eintrag. Sie erhalten Hinweise, wenn ein Marktplatz es aufnimmt, entfernt, sein Verified-Zeichen oder seine Anforderungen ändert, und sein Remote-Endpunkt wird wie ein Webdienst überwacht.
Daten von Official MCP Registry. Die Zahlen stammen aus unseren eigenen regelmäßigen Durchläufen über die Marktplätze, zuletzt abgerufen am . Kontaktdaten von Plugin-Herausgebern veröffentlichen wir nicht.