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: Multi-Model Advisor

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

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)

2. Install Dependencies

3. Install and Start Ollama

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

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)

Option 2: Using Python Startup Script

Option 3: Direct Execution

Option 4: Development Mode

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

Test the Server

Configuration

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

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