Prometheus Mcp — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Prometheus Mcp (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Prometheus Main
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AI Creative Director that turns ordinary model output into expert-level work.
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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.
사용자 요청
-> Planner
-> Knowledge Collector
-> Pattern Selector
-> Prompt Enhancer
-> Generation Provider
-> Evidence Collector
-> Critic Engine
-> Quality Scoring
-> Improvement Engine
-> Regeneration Loop
-> 최종 결과| 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 |
| 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 |
npm install
npm run build
npm start프로젝트 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_config.json에 추가:
{
"mcpServers": {
"prometheus": {
"command": "node",
"args": ["E:/Downloads/Prometheus-MCP/dist/index.js"]
}
}
}npm test환경 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.
MIT
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.
User request
-> Planner
-> Knowledge Collector
-> Pattern Selector
-> Prompt Enhancer
-> Generation Provider
-> Evidence Collector
-> Critic Engine
-> Quality Scoring
-> Improvement Engine
-> Regeneration Loop
-> Final result| 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 |
| 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 |
npm install
npm run build
npm startCreate 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.
Add to claude_desktop_config.json:
{
"mcpServers": {
"prometheus": {
"command": "node",
"args": ["E:/Downloads/Prometheus-MCP/dist/index.js"]
}
}
}npm testEnvironment 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.
MIT
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.