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

Related MCP server: Ollama MCP Proxy

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)

conda create -n openbanking-backend python=3.11
conda activate openbanking-backend

2. Install Dependencies

pip install -r requirements.txt

3. Install and Start Ollama

Download and install Ollama from https://ollama.ai

# 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)

.\start_server.ps1

Option 2: Using Python Startup Script

python startup.py

Option 3: Direct Execution

conda activate openbanking-backend
python src/main.py

Option 4: Development Mode

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

python demo.py

Test the Server

python test_server.py

Configuration

The server uses config/config.yaml for configuration. Key sections:

# 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