Raiffeisenbank München-Süd MCP Server

Bank account information including account details, balances, and metadata

Transaction history including debits, credits, and transaction details

Current and available account balances

Get the complete database schema including all tables, columns, data types, and descriptions for your financial data. This should be your first step before querying data - it shows you exactly what tables and fields are available (accounts, transactions, balances, etc.). Essential for understanding your data structure before writing queries.

Refresh and synchronize your financial data from the bank connection. This fetches the latest transactions, balances, and account information from your connected bank account and updates your local database cache. Use this when you want to ensure you're working with the most up-to-date financial data.

Query your financial data using natural language or SQL. Ask questions like 'What was my spending last month?' or 'Show me all transactions over £500'. The AI will automatically convert your question into optimized SQL queries and execute them against your banking data.

Gets a distinct list of values for a specified column in the financial data tables (accounts, transactions, balances). Useful for understanding what categories, account types, or other dimensions exist in your data.

Provides documentation and help for DuckDB SQL syntax and functions. Use this when you need help writing queries or understanding DuckDB-specific features.

Validates SQL syntax and provides corrections if issues are found. Use this before executing complex queries to catch syntax errors.

Execute a SQL query against your financial data and return the first 3 rows. Use this to preview query results before running the full query to avoid memory issues.

Create a category lookup table from an existing field in your transactions. Useful for categorizing transactions by merchant, description patterns, or amount ranges.

Search through pre-built financial analysis workflow templates using natural language. Get step-by-step guidance for common tasks like calculating profit/loss, generating spending reports, identifying unusual patterns, cash flow analysis, and more. Uses AI-powered semantic search to find relevant workflows from a library of proven financial analysis examples.