The Adaptive MCP (Model Context Protocol) Server is an advanced AI reasoning system designed to provide intelligent, multi-strategy solutions to complex questions. By combining multiple reasoning approaches, real-time research, and comprehensive validation, this system offers a sophisticated approach to information processing and answer generation.
Multi-Strategy Reasoning
Advanced Research Integration
Comprehensive Validation
## Clone the repository
git clone https://github.com/your-org/adaptive-mcp-server.git
## Create virtual environment
python -m venv venv
source venv/bin/activate # On Windows, use `venv\Scripts\activate`
## Install dependencies
pip install -r requirements.txt
from reasoning import reasoning_orchestrator
async def main():
# Ask a complex question
result = await reasoning_orchestrator.reason(
"What are the potential long-term impacts of artificial intelligence?"
)
print(result['answer'])
print(f"Confidence: {result['confidence']}")
Create a mcp_config.json in the project root:
{
"research": {
"api_key": "YOUR_EXA_SEARCH_API_KEY",
"max_results": 5,
"confidence_threshold": 0.6
},
"reasoning": {
"strategies": [
"sequential",
"branching",
"abductive"
]
}
}
from reasoning import reasoning_orchestrator, ReasoningStrategy
## Customize strategy selection
custom_strategies = [
ReasoningStrategy.LOGICAL,
ReasoningStrategy.LATERAL
]
## Use specific strategies
result = await reasoning_orchestrator.reason(
"Design an innovative solution to urban transportation",
strategies=custom_strategies
)
## Run all tests
pytest tests/
## Run specific module tests
pytest tests/test_research.py
pytest tests/test_orchestrator.py
git checkout -b feature/AmazingFeature)git commit -m 'Add some AmazingFeature')git push origin feature/AmazingFeature)confidence field in resultsDistributed under the MIT License. See LICENSE for more information.
Your Name - [email protected]
Project Link: https://github.com/your-org/adaptive-mcp-server
