OpenBanking MCP Server

# OpenBanking MCP Server An MCP (Model Context Protocol) server that integrates with local Ollama LLMs for OpenBanking applications. ## Features - **Multiple LLM Agents**: Support for 4 different specialized agents - **Ollama Integration**: Local LLM model support - **Tool System**: Comprehensive toolset for various operations - **OpenBanking Focus**: Specialized tools for banking and financial data ## Architecture This MCP server follows the architecture shown in the diagram: - MCP Host communicates with MCP Server - 4 Specialized Agents (Agent 1-4) with LLM/Model capabilities - Tool system for specific operations - Banking Services/API integration ## Agents 1. **Agent 1 - Market Analyst**: Market data analysis and volatile situations 2. **Agent 2 - Portfolio Manager**: Portfolio management and strategy finding 3. **Agent 3 - Risk Analyst**: Risk analysis for users 4. **Agent 4 - Explainability Agent**: LLM for explainability and SWOT analysis ## Project Structure ``` mcpOpenbankingMCPServer/ ├── src/ │ ├── __init__.py │ ├── main.py # Main server entry point │ ├── agents/ │ │ ├── __init__.py │ │ └── agent_manager.py # Agent management system │ ├── tools/ │ │ ├── __init__.py │ │ ├── tool_registry.py # Tool registration and management │ │ ├── portfolio_tools.py # Portfolio analysis tools │ │ ├── market_tools.py # Market data tools │ │ ├── risk_tools.py # Risk assessment tools │ │ ├── strategy_tools.py # Strategy recommendation tools │ │ └── analysis_tools.py # SWOT and explanation tools │ ├── config/ │ │ ├── __init__.py │ │ └── config.py # Configuration management │ └── utils/ │ ├── __init__.py │ └── utils.py # Utility functions ├── config/ │ └── config.yaml # Server configuration ├── requirements.txt # Python dependencies ├── startup.py # Python startup script ├── start_server.ps1 # PowerShell startup script ├── start_server.bat # Batch file for Windows ├── demo.py # Demo examples ├── test_server.py # Test script └── README.md # This file ``` ## Prerequisites 1. **Python 3.8+** with conda environment 2. **Ollama** installed and running locally 3. **Conda environment** named `openbanking-backend` ## Setup ### 1. Create Conda Environment (if not exists) ```bash conda create -n openbanking-backend python=3.11 conda activate openbanking-backend ``` ### 2. Install Dependencies ```bash pip install -r requirements.txt ``` ### 3. Install and Start Ollama Download and install Ollama from [https://ollama.ai](https://ollama.ai) ```bash # Pull a model (example with Llama 3.2) ollama pull llama3.2:latest # Start Ollama server ollama serve ``` ### 4. Configure the Server Edit `config/config.yaml` to customize: - Ollama connection settings - Agent configurations - Model assignments - Tool settings ## Running the Server ### Option 1: Using PowerShell Script (Recommended for Windows) ```powershell .\start_server.ps1 ``` ### Option 2: Using Python Startup Script ```bash python startup.py ``` ### Option 3: Direct Execution ```bash conda activate openbanking-backend python src/main.py ``` ### Option 4: Development Mode ```bash python src/main.py --dev ``` ## Tools Available ### Portfolio Analysis - `analyze_portfolio`: Comprehensive portfolio analysis - `portfolio_optimization`: Portfolio allocation optimization ### Market Analysis - `market_analysis`: Current market conditions analysis - `volatility_analysis`: Market volatility assessment ### Risk Assessment - `assess_risk`: User-specific risk assessment - `risk_simulation`: Scenario-based risk simulation ### Strategy Recommendations - `recommend_strategy`: Investment strategy recommendations ### Analysis & Explainability - `swot_analysis`: SWOT analysis for any subject - `explain_concept`: Explain financial concepts simply - `reverse_simulation`: Reverse engineering analysis ## Usage Examples ### Run Demo ```bash python demo.py ``` ### Test the Server ```bash python test_server.py ``` ## Configuration The server uses `config/config.yaml` for configuration. Key sections: ```yaml # Ollama connection ollama: host: "localhost" port: 11434 timeout: 30 # Agents configuration agents: - name: "market_analyst" model: "gemma3:4b" role: "Market Data Analyst" # ... more config # Tools configuration tools: - name: "portfolio_analysis" enabled: true ``` ## Troubleshooting ### Common Issues 1. **Ollama Connection Failed** - Ensure Ollama is installed and running (`ollama serve`) - Check if the default port 11434 is available - Verify models are pulled (`ollama list`) 2. **Conda Environment Issues** - Make sure `openbanking-backend` environment exists - Activate the environment before running - Install dependencies in the correct environment 3. **Import Errors** - Ensure all dependencies are installed - Check Python path and working directory ### Logs Check the console output for detailed error messages and debugging information. ## Development ### Adding New Tools 1. Create tool class in `src/tools/` 2. Add tool registration in `tool_registry.py` 3. Update configuration if needed ### Adding New Agents 1. Add agent configuration in `config/config.yaml` 2. Implement custom agent logic if needed 3. Test with demo scripts ## License MIT License