Adaptive MCP Server

🚀 Adaptive MCP Server

The Adaptive MCP (Model Context Protocol) Server is an advanced AI inference system. It aims to provide intelligent and multi - strategy solutions for complex problems by combining various inference methods, real - time research, and comprehensive verification. This system, which uses a comprehensive approach to information processing and answer generation, represents the latest advancements in the field of artificial intelligence.

✨ Features

Multi - Strategy Inference

• Sequential reasoning
• Branching reasoning
• Abductive reasoning
• Lateral (creative) reasoning
• Logical reasoning

Advanced Research Integration

• Real - time information retrieval
• Support for multiple search strategies
• Confidence - based result verification

Comprehensive Verification

• Semantic similarity check
• Fact accuracy assessment
• Confidence scoring
• Error detection

📦 Installation

Prerequisites

• Python 3.8+
• pip package manager
• It is recommended to use a virtual environment

Setup Steps

# Clone the repository
git clone https://github.com/your-org/adaptive-mcp-server.git

# Create a virtual environment
python -m venv venv
source venv/bin/activate  # On Windows, use `venv\Scripts\activate`

# Install dependencies
pip install -r requirements.txt

🚀 Quick Start

Basic Usage

from reasoning import reasoning_orchestrator

async def main():
    # Pose a complex question
    result = await reasoning_orchestrator.reason(
        "What are the long - term potential impacts of artificial intelligence?"
    )
    
    print(result['answer'])
    print(f"Confidence: {result['confidence']}")

Configuration Guide

Create the mcp_config.json file in the project root directory:

{
    "research": {
        "api_key": "YOUR_EXA_SEARCH_API_KEY",
        "max_results": 5,
        "confidence_threshold": 0.6
    },
    "reasoning": {
        "strategies": [
            "sequential", 
            "branching", 
            "abductive"
        ]
    }
}

💻 Usage Examples

Basic Usage

from reasoning import reasoning_orchestrator

async def main():
    # Pose a complex question
    result = await reasoning_orchestrator.reason(
        "What are the long - term potential impacts of artificial intelligence?"
    )
    
    print(result['answer'])
    print(f"Confidence: {result['confidence']}")

Advanced Usage

Customized Reasoning Strategies

from reasoning import reasoning_orchestrator, ReasoningStrategy

# Customize strategy selection
custom_strategies = [
    ReasoningStrategy.LOGICAL, 
    ReasoningStrategy.LATERAL
]

# Perform reasoning using specific strategies
result = await reasoning_orchestrator.reason(
    "Design an innovative urban transportation solution",
    strategies=custom_strategies
)

📚 Documentation

Development Information

Run Tests

# Execute all tests
pytest tests/

# Run tests for a specific module
pytest tests/test_research.py
pytest tests/test_orchestrator.py

Contribution Guide

1. Fork the repository
2. Create a feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add AmazingFeature')
4. Push the branch (git push origin feature/AmazingFeature)
5. Submit a pull request

Best Practices

• Modular Design: Break the code into independent components to improve maintainability and scalability.
• Error Handling: Add exception catching and logging in critical operations to ensure system stability.
• Verification and Testing: Cover all functional paths with comprehensive test cases to guarantee product quality.

Troubleshooting

• Environment Configuration Errors: Check if the Python version meets the requirements (3.8+) and confirm that the dependencies are installed correctly.
• API Request Failures: Verify the validity of the API key and ensure a normal network connection.
• Poor Performance: Optimize the code logic to reduce unnecessary computations and resource consumption.

📄 License

This project is licensed under the MIT License. Please refer to the LICENSE file for specific terms.

Contact

If you have any questions or suggestions, please contact us at contact@yourorganization.com