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Prometheus-MCP

by gguatit

Prometheus Main

Prometheus-MCP

Creative Director MCP

AI Creative Director that turns ordinary model output into expert-level work.

한국어 | English


한국어

Prometheus-MCP는 Claude, GPT, DeepSeek, MiniMax, Qwen, GLM 및 미래 모델이 생성한 크리에이티브 산출물을 전문가 수준으로 끌어올리는 Model Context Protocol 서버입니다. 단순한 문서 검색 시스템이 아니라, 생성 - 평가 - 개선 - 재생성 루프를 통해 품질을 지속적으로 향상시키는 AI Creative Director입니다.

대상 분야

  • 웹 디자인 / UI 디자인 / UX 디자인

  • Three.js / React Three Fiber / WebGL / WebGPU

  • VFX / 셰이더 (GLSL / WGSL) / 인터랙티브 경험

  • 프론트엔드 애니메이션 / 크리에이티브 코딩

  • 게임 개발 (2D / 3D / Phaser / Rapier / ECS)

핵심 가치

  1. 전문가 패턴 라이브러리 - 22개 패턴, 확장 가능한 구조

  2. Critic Engine - 16개 품질 차원, 60개 규칙, 증거 기반 평가

  3. 자동 개선 루프 - 목표 점수 도달까지 반복

  4. 품질 인텔리전스 - 감사 가능한 점수 근거

  5. AI 크리에이티브 디렉팅 - 패턴 선택, 개선 전략, 재생성

아키텍처

사용자 요청
  -> Planner
  -> Knowledge Collector
  -> Pattern Selector
  -> Prompt Enhancer
  -> Generation Provider
  -> Evidence Collector
  -> Critic Engine
  -> Quality Scoring
  -> Improvement Engine
  -> Regeneration Loop
  -> 최종 결과

모듈

모듈

역할

planner

도메인 탐지, 브리프 생성, 종료 정책

knowledge

외부 지식 수집 + 프롬프트 인젝션 방어

patterns

패턴 검증, 저장소, 가중치 기반 선택

critic

증거 수집(결정적 측정) + 규칙 평가 + 점수 + 감사 가능 근거

improver

부분/전체 재생성 전략, 수정 프롬프트

loop_controller

상태 머신 + 종료 정책(목표/최대반복/비용/시간/수익체감)

providers

역량 기반 라우터 (Stub, OpenAI 호환, Claude)

memory

세션 간 학습, 효과성 추적

history

세션 내 타임라인

telemetry

구조화 로그, 메트릭, 비용, 트레이싱, 비밀 마스킹

infrastructure

설정, 캐시, 보안

mcp

7 tools / 5 resources / 4 prompts

MCP 도구

도구

설명

direct_creative_work

브리프에서 생성-평가-개선 루프 실행

critique_artifact

산출물 평가 (점수, 강점, 약점, 제안)

improve_artifact

평가 기반 개선 계획 + 수정 프롬프트

list_patterns

패턴 목록 조회

get_pattern

패턴 상세 조회

recall_sessions

과거 세션 조회

get_quality_trends

품질 추세 분석

설치 및 실행

npm install
npm run build
npm start

opencode 로컬 MCP 연결

프로젝트 루트에 opencode.json을 생성하고 Prometheus를 로컬 MCP로 등록합니다. API 키 불필요 (StubProvider 기본 활성화).

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "prometheus": {
      "type": "local",
      "command": ["node", "E:/Downloads/Prometheus-MCP/dist/index.js"],
      "enabled": true
    }
  }
}

opencode 재시작 후 7개 도구(direct_creative_work, critique_artifact 등)가 에이전트에 연결됩니다.

Claude Desktop 연결

claude_desktop_config.json에 추가:

{
  "mcpServers": {
    "prometheus": {
      "command": "node",
      "args": ["E:/Downloads/Prometheus-MCP/dist/index.js"]
    }
  }
}

테스트

npm test

설정

환경 변수로 런타임 설정을 덮어쓸 수 있습니다.

변수

설명

PROMETHEUS_TARGET_SCORE

목표 품질 점수 (기본 85)

PROMETHEUS_MAX_ITERATIONS

최대 개선 반복 (기본 5)

PROMETHEUS_MAX_COST_USD

비용 상한 (USD)

PROMETHEUS_DEFAULT_PROVIDER

기본 모델 제공자

PROMETHEUS_ENABLE_LLM_REASONING

LLM 추론 평가 활성화

PROMETHEUS_ALLOW_COMMUNITY_PATTERNS

커뮤니티 패턴 허용

모델 제공자 API 키는 해당 환경 변수(OPENAI_API_KEY, ANTHROPIC_API_KEY, DEEPSEEK_API_KEY 등)가 존재하면 자동 활성화됩니다.

기술 스택

  • TypeScript (ES Modules)

  • Node.js 20+

  • @modelcontextprotocol/sdk 1.29.0 (안정版)

  • zod v3 / ajv

  • Vitest

라이선스

MIT


Related MCP server: Prompt Auto-Optimizer MCP

English

Prometheus-MCP is a Model Context Protocol server that elevates creative output from Claude, GPT, DeepSeek, MiniMax, Qwen, GLM, and future models to expert-level quality. It is not a document retrieval system. It is an AI Creative Director that runs a generate - critique - improve - regenerate loop to continuously raise quality.

Target Domains

  • Web design / UI design / UX design

  • Three.js / React Three Fiber / WebGL / WebGPU

  • VFX / shaders (GLSL / WGSL) / interactive experiences

  • Frontend animation / creative coding

  • Game development (2D / 3D / Phaser / Rapier / ECS)

Core Value

  1. Expert Pattern Library - 22 patterns, extensible structure

  2. Critic Engine - 16 quality dimensions, 60 rules, evidence-bound evaluation

  3. Auto Improvement Loop - iterates until target score is reached

  4. Quality Intelligence - auditable score justifications

  5. AI Creative Directing - pattern selection, improvement strategy, regeneration

Architecture

User request
  -> Planner
  -> Knowledge Collector
  -> Pattern Selector
  -> Prompt Enhancer
  -> Generation Provider
  -> Evidence Collector
  -> Critic Engine
  -> Quality Scoring
  -> Improvement Engine
  -> Regeneration Loop
  -> Final result

Modules

Module

Responsibility

planner

domain detection, brief formation, termination policy

knowledge

external knowledge collection + prompt injection defense

patterns

pattern validation, repository, weighted selection

critic

evidence collection (deterministic measurement) + rule evaluation + scoring + auditable justification

improver

surgical/full regeneration strategy, revision prompts

loop_controller

state machine + termination policy (target/maxIter/cost/wallClock/diminishing returns)

providers

capability-based router (Stub, OpenAI-compatible, Claude)

memory

cross-session learning, effectiveness tracking

history

intra-session timeline

telemetry

structured logs, metrics, cost, tracing, secret redaction

infrastructure

config, cache, security

mcp

7 tools / 5 resources / 4 prompts

MCP Tools

Tool

Description

direct_creative_work

runs generate-critique-improve loop from a brief

critique_artifact

evaluates an artifact (score, strengths, weaknesses, suggestions)

improve_artifact

builds improvement plan + revision prompt from a critique

list_patterns

lists available patterns

get_pattern

gets pattern detail

recall_sessions

recalls past sessions

get_quality_trends

analyzes quality trends

Install and Run

npm install
npm run build
npm start

opencode Local MCP

Create opencode.json in your project root and register Prometheus as a local MCP. No API key needed (StubProvider enabled by default).

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "prometheus": {
      "type": "local",
      "command": ["node", "E:/Downloads/Prometheus-MCP/dist/index.js"],
      "enabled": true
    }
  }
}

Restart opencode and the 7 tools (direct_creative_work, critique_artifact, etc.) become available to the agent.

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "prometheus": {
      "command": "node",
      "args": ["E:/Downloads/Prometheus-MCP/dist/index.js"]
    }
  }
}

Tests

npm test

Configuration

Environment variables override runtime config.

Variable

Description

PROMETHEUS_TARGET_SCORE

target quality score (default 85)

PROMETHEUS_MAX_ITERATIONS

max improvement iterations (default 5)

PROMETHEUS_MAX_COST_USD

cost cap (USD)

PROMETHEUS_DEFAULT_PROVIDER

default model provider

PROMETHEUS_ENABLE_LLM_REASONING

enable LLM reasoning in critique

PROMETHEUS_ALLOW_COMMUNITY_PATTERNS

allow community-trust patterns

Model provider API keys auto-enable their providers when the corresponding env var (OPENAI_API_KEY, ANTHROPIC_API_KEY, DEEPSEEK_API_KEY, etc.) is present.

Tech Stack

  • TypeScript (ES Modules)

  • Node.js 20+

  • @modelcontextprotocol/sdk 1.29.0 (stable)

  • zod v3 / ajv

  • Vitest

License

MIT

A
license - permissive license
-
quality - not tested
B
maintenance

Maintenance

Maintainers
Response time
Release cycle
Releases (12mo)
Commit activity

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