AI Orchestrator

AI Orchestrator

Enables multi-strategy AI orchestration including council decision review, debate, brainstorming, evaluation, and spec review, with support for multiple LLM providers and advisor personas.

Category
访问服务器

README

🤖 AI Orchestrator

Advanced AI orchestration engine — multi-advisor councils, structured debates, creative brainstorming, and multi-criteria evaluation. Works as an MCP (Model Context Protocol) server with any compatible AI tool.

Supports: OpenCode, Claude Code, Cursor, Windsurf, Continue, Cline, Copilot, and any MCP-compatible client.


✨ Features

5 Orchestration Strategies

Strategy Description Use Case
Council 🏛️ Multi-advisor decision review with anonymous peer evaluation (Karpathy method) Critical decisions, risk assessment
Debate ⚔️ Structured pro/con debate with judge verdict Go/no-go decisions, tradeoff analysis
Brainstorm 💡 Creative idea generation with scoring and clustering Feature discovery, product innovation
Evaluate 📊 Multi-criteria option scoring with weighted analysis Vendor selection, tech choices
Spec Review 🔍 Specialist review from multiple angles (security, UX, DevOps, etc.) Pre-implementation plan review

15+ Advisor Personas

Persona Stance Specialty Language
Skeptic (Muhalif) Critical Risk detection, failure modes EN / TR
First Principles (İlk İlkeler) Analytical Assumption deconstruction EN / TR
Expansionist (Genişlemeci) Creative Opportunity discovery EN / TR
Outsider (Yabancı) Neutral Jargon-free fresh eyes EN / TR
Executor (İcracı) Practical Implementation, first steps EN / TR
Visionary Creative Future opportunities
Pragmatist Practical Feasibility, resource constraints
Security Auditor Critical Attack surfaces, data exposure
UX Advocate Critical User journey, accessibility
Business Analyst Analytical ROI, market positioning
DevOps Engineer Practical Deployability, scaling
Ethicist Analytical Fairness, societal impact
Architect Analytical System design, patterns
Tester Critical Edge cases, testability
Growth Hacker Creative Metrics, viral loops

Turkish advisors (Muhalif, İlk İlkeler, Genişlemeci, Yabancı, İcracı) are available for Turkish-language decisions. The rest respond in English by default but support any language the question is asked in.

Pre-built Councils

Council Advisors Language Use Case
Executive Board Skeptic, Visionary, Pragmatist, Security, Business, UX EN General business decisions
Akıl Kurulu Muhalif, İlk İlkeler, Genişlemeci, Yabancı, İcracı TR Turkish-language decisions
Tech Review Architect, Security, DevOps, Tester EN Architecture/stability review
Ethics Board Ethicist, UX, Skeptic, Business EN Ethical impact assessment
Quick Check Skeptic, Pragmatist, Visionary EN Fast 3-advisor decision

Multi-Provider Support

Provider Setup
OpenAI OPENAI_API_KEY
Anthropic (Claude) ANTHROPIC_API_KEY
OpenRouter OPENROUTER_API_KEY
Ollama (local) No key needed — just run ollama serve
Groq GROQ_API_KEY
Google (Gemini) GOOGLE_API_KEY
DeepSeek DEEPSEEK_API_KEY

🚀 Quick Start

Prerequisites

  • Node.js 18+
  • At least one LLM provider API key (or Ollama running locally)

Install & Configure

# Clone
git clone https://github.com/YOUR_USER/ai-orchestrator.git
cd ai-orchestrator

# Install
npm install
npm run build

# Configure at least one provider
export OPENAI_API_KEY="sk-..."
# OR
export ANTHROPIC_API_KEY="sk-ant-..."
# OR run Ollama locally: ollama serve

Add to Your AI Tool

OpenCode

// opencode.json
{
  "mcpServers": {
    "ai-orchestrator": {
      "command": "node",
      "args": ["/path/to/ai-orchestrator/dist/index.js"],
      "env": {
        "OPENAI_API_KEY": "${OPENAI_API_KEY}"
      }
    }
  }
}

Claude Code

// .claude/mcp.json
{
  "mcpServers": {
    "ai-orchestrator": {
      "command": "node",
      "args": ["/path/to/ai-orchestrator/dist/index.js"],
      "env": {
        "ANTHROPIC_API_KEY": "${ANTHROPIC_API_KEY}"
      }
    }
  }
}

Cursor / Windsurf

Add to Cursor MCP settings or .cursor/mcp.json:

{
  "mcpServers": {
    "ai-orchestrator": {
      "command": "node",
      "args": ["/absolute/path/to/ai-orchestrator/dist/index.js"]
    }
  }
}

📖 Usage

Once configured, call any tool from your AI assistant:

Council (Decision Review)

Use the orchestrate tool to review: "Should we rewrite our Bootstrap themes to Tailwind?"

Strategy: council
Council: executive_board

Returns: 6 independent advisor opinions → anonymous peer review → chairman synthesis with recommendations.

Debate (Pro/Con Analysis)

Orchestrate a debate on: "Should we adopt microservices?"

Strategy: debate
Rounds: 3

Brainstorm (Idea Generation)

Brainstorm ideas for: "How to improve developer onboarding?"

Strategy: brainstorm

Evaluate (Option Scoring)

Evaluate these database options: PostgreSQL, MongoDB, Supabase
Criteria: Performance (0.4), Ease of Use (0.3), Cost (0.3)

Strategy: evaluate

Spec Review (Plan Audit)

Review this architecture spec from security, performance, and UX perspectives.

Strategy: spec-review

🔧 Architecture

src/
├── index.ts          # MCP Server entry point (4 tools exposed)
├── types.ts          # TypeScript type definitions
├── personas.ts       # 15+ advisor personas + 5 council presets
├── providers.ts      # LLM provider layer (7 providers)
└── strategies/
    ├── council.ts    # Karpathy 3-stage multi-advisor council
    ├── debate.ts     # Structured pro/con debate with judge
    ├── brainstorm.ts # Creative brainstorming with clustering
    └── evaluate.ts   # Multi-criteria evaluation + spec review

Council Flow (Karpathy Method)

                    ┌─────────────┐
                    │  Question   │
                    └──────┬──────┘
            ┌──────────────┼──────────────┐
      ┌─────▼─────┐ ┌─────▼─────┐ ┌─────▼─────┐
      │ Advisor A │ │ Advisor B │ │ Advisor N │  ← Parallel (isolated)
      │ (Skeptic) │ │(Visionary)│ │  (...)    │
      └─────┬─────┘ └─────┬─────┘ └─────┬─────┘
            └──────────────┼──────────────┘
                     ┌─────▼─────┐
                     │ Anonymize │              ← Anonymous review
                     └─────┬─────┘
            ┌──────────────┼──────────────┐
      ┌─────▼─────┐ ┌─────▼─────┐ ┌─────▼─────┐
      │ Peer Rev A│ │ Peer Rev B│ │ Peer Rev N│
      └─────┬─────┘ └─────┬─────┘ └─────┬─────┘
            └──────────────┼──────────────┘
                     ┌─────▼─────┐
                     │ Chairman  │              ← Synthesis
                     │ Verdict   │
                     └───────────┘

🌐 Multi-Language Support

The system is English-first but fully multi-language:

  • Executive Board, Tech Review, Ethics Board, Quick Check → English by default
  • Akıl Kurulu → Turkish advisors for Turkish-language decisions
  • You can ask questions in any language — the system matches the input language
  • Advisors defined in Turkish (Muhalif, İlk İlkeler, etc.) will respond in Turkish when used
  • The simulation mode (no API keys) also supports any language the calling AI understands

🛠️ Development

npm install        # Install dependencies
npm run build      # Compile TypeScript
npm run dev        # Watch mode
npm start          # Run server directly

📄 License

MIT — see LICENSE


🙏 Credits


Made for AI-powered decision making. Ship with confidence.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选