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AI Council MCP Server

by 0xAkuti

AI Council MCP Server

Multi-AI Consensus Tool: Query multiple AI models in parallel, synthesize responses for better accuracy, and reduce AI bias through ensemble decision-making.

AI Council is a powerful MCP (Model Context Protocol) server that harnesses the "wisdom of crowds" by consulting multiple AI models simultaneously. Get more reliable, comprehensive answers by combining insights from OpenAI, Claude, Gemini, and any OpenAI-compatible API.

✨ What is AI Council?

AI Council transforms how you interact with AI by:

  • 🔄 Parallel Processing: Queries multiple AI models simultaneously (not sequentially)

  • 🎯 Bias Reduction: Uses anonymous code names to prevent synthesis bias

  • ⚡ Smart Synthesis: One model synthesizes all responses into a comprehensive answer

  • 🔧 Universal Compatibility: Works with OpenAI, OpenRouter, and any OpenAI-compatible API

  • 🛡️ Robust Error Handling: Graceful degradation when individual models fail

Perfect for: Research questions, complex analysis, creative projects, technical decisions, and any task where multiple AI perspectives add value.

Related MCP server: polydev-ai

📋 Requirements

  • Python 3.10+

  • uv installed (installation guide)

  • alternatively:

    • pipx installed (installation guide), update config

        "command": "pipx",
        "args": ["run", "ai-council"]
    • or manual install wiht pip install ai-council, and update config

      "command": "ai-council",
      "args": []

🚀 Quick Start

  1. Get your OpenRouter api key

Cursor IDE Setup

  1. Open Cursor Settings → MCP

  2. Add new MCP server and set your api key:

{
  "ai-council": {
    "command": "uvx",
    "args": ["ai-council"],
    "env": {
      "OPENROUTER_API_KEY": "..."
    }
  }
}

Claude Desktop Setup

  1. Edit ~/.claude_desktop_config.json and set your api key:

{
  "mcpServers": {
    "ai-council": {
      "command": "uvx",
      "args": ["ai-council"],
      "env": {
        "OPENROUTER_API_KEY": "..."
      }
    }
  }
}

That's it! Ask any complex question and the AI Council tool will automatically engage multiple models.

By default it will use OpenRouter with Claude Sonnet 4, Gemini 2.5 Pro, and DeepSeek V3.

CLI Arguments

Use command-line arguments for quick setup, add any of these to the args in you mcp config:

Available CLI Arguments:

  • --openai-api-key: Your OpenAI API key

  • --openrouter-api-key: Your OpenRouter API key

  • --max-models: Maximum models to query (default: 3)

  • --parallel-timeout: Timeout in seconds (default: 60)

  • --log-level: Logging level (DEBUG, INFO, WARNING, ERROR)

  • --config: Path to custom config file

⚙️ Advanced Configuration

For advanced setups, create a config.yaml file and link to it with --config path/to/config.yaml:

# config.yaml
openai_api_key: "your_openai_key_here"
openrouter_api_key: "your_openrouter_key_here"
max_models: 3
parallel_timeout: 90 # in seconds
synthesis_model_selection: "random"  # or "first"

models:
  # use OpenAI API
  - name: "GPT-4o"
    provider: "openai" 
    model_id: "gpt-4o"
    enabled: true # optional, defaults to true
    
  # use OpenRouter API
  - name: "Claude Sonnet"
    provider: "openrouter"
    model_id: "anthropic/claude-3.5-sonnet"
    code_name: "Bob" # optional, auto assigned otherwise
  
  # or any custom OpenAI compatible API
  - name: "Perplexity"
    provider: "custom"
    model_id: "llama-3.1-sonar-large-128k-online"
    base_url: "https://api.perplexity.ai"
    api_key: "your_perplexity_key_here"
    
  # Local LLM (Ollama)
  - name: "Local Llama"
    provider: "custom" 
    model_id: "llama-3b"
    base_url: "http://localhost:11434"
    api_key: "key-if-needed"

📖 How It Works

AI Council uses a sophisticated three-phase approach:

1. Parallel Consultation

  • Simultaneously queries your configured AI models

  • Maintains the same context and question for each model

  • Handles failures gracefully (continues with successful responses)

2. Anonymous Analysis

  • Assigns code names (Alpha, Beta, Gamma, etc.) to each model's response

  • Prevents synthesis bias toward specific brands or providers

  • Preserves response quality while removing model identity

3. Smart Synthesis

  • Randomly selects one model to act as the synthesizer

  • Synthesizer analyzes all anonymous responses

  • Produces a comprehensive answer combining the best insights

🤝 Acknowledgments

This project was inspired by Cognition Wheel.

AI Council extends these ideas with:

  • Enhanced configuration flexibility

  • OpenRouter support for many model options with a single api key

  • Support for custom API endpoints

  • Improved error handling and logging

  • Using Python

Available Tools

1 tool
ai_councilA

A tool that consults multiple AI models in parallel, then uses one of them to synthesize the results into a single, high-quality answer. Use this for complex questions requiring deep analysis and verification.

ParametersJSON Schema
NameRequiredDescriptionDefault
contextYesImportant background information and context for the problem to be solved.
questionYesThe specific, detailed question you want to be answered.

TDQS

A4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It discloses parallel consultation and synthesis behavior, but does not mention read-only nature, rate limits, or potential slowness. The behavioral traits are partially but not completely revealed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, each earning its place. First describes what the tool does, second advises when to use it. No extraneous words or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given two simple parameters and no output schema, the description adequately explains the tool's purpose and behavior. The return is described as 'single, high-quality answer,' which is sufficient for a query tool. Could be more specific about output format but overall complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description does not add any parameter-specific meaning beyond the schema definitions. No additional semantics are provided.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool consults multiple AI models in parallel and synthesizes results into one answer, with specific verb+resource (consult+synthesize, produce answer). It distinguishes itself by targeting complex questions requiring deep analysis and verification.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Use this for complex questions requiring deep analysis and verification,' providing clear context for when to use the tool. No alternatives or when-not cases are given, but the context is sufficient given no sibling tools exist.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev0.2.3
    • First observedai_council

TDQS

A3.9/5.0

Scored across 1 tool

Disambiguation5/5

Only one tool exists, so there is no possibility of ambiguity between tools.

Naming Consistency5/5

With a single tool (ai_council), naming consistency is not an issue; the name follows a clear snake_case pattern.

Tool Count2/5

Having only one tool feels thin for a server named 'AI Council MCP Server', as it limits functionality to a single action without auxiliary or configuration tools.

Completeness2/5

The tool covers a specific synthesis task, but the server lacks other potentially useful tools like model configuration, result handling, or iterative analysis, leaving notable gaps.

Maintenance

ActivityInactive
ResponsivenessNo issues

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