N26 Banking MCP. Get real-time balances and transaction data directly into your chat.

You're tired of bouncing between apps just to check your money, right? This MCP Server lets your agent pull real-time financial data straight from N26. You don't gotta log into a browser or juggle multiple banking dashboards; your AI client handles it all.

The core functionality lives in three tools: get_n26_accounts, get_n26_spaces, and get_n26_transactions. These aren't just basic read operations; they give your agent the full picture of where your money is, how much you have, and exactly where it went across the Eurozone.

When you need a quick status check, the agent uses get_n26_accounts to list every N26 account you own. You get back the current balance and the IBAN for each one instantly. This means your AI client knows your full banking footprint without you lifting a finger. It's fast.

Need to keep track of that cash for the big purchase or the trip? The tool get_n26_spaces handles that. It retrieves the current balance for any dedicated sub-accounts—those savings goals, what N26 calls 'Spaces.' You can see how much money's sitting in your 'Vacation Fund' or whatever else you earmarked it for.

To audit your spending habits, the agent runs get_n26_transactions. This tool pulls a detailed list of recent activity. It doesn't just give you dates; it details vendor names and precise amounts for every transaction that hit your accounts in the Eurozone.

When these tools work together, they let your AI client generate actual financial summaries. You can ask it to synthesize data from all three endpoints—for instance, 'How much did I spend on groceries last month?' The agent cross-references the spending history provided by get_n26_transactions with the overall balances listed by get_n26_accounts, giving you a precise answer without needing manual calculations.

You can ask it to check your total balance across all active accounts using get_n26_accounts, and then immediately verify if that combined amount is enough to cover the next withdrawal date, pulling in data from both the main account balances and any dedicated 'Spaces' via get_n26_spaces. It’s about mechanical efficiency.

If you want a detailed breakdown of how much money left your card for specific categories—say, utilities or gas—the agent pulls that granular data through the transaction list provided by get_n26_transactions and formats it for immediate review. You don't have to manually categorize anything; the AI client handles the parsing of vendor names and amounts from the raw feed.

This setup means you get a complete, chronological picture of your money flow, identifying every debit and credit across all accounts simultaneously. It’s simple access to complex data sets. You can ask it for a summary comparing spending between two different months, using the detailed transaction history available through get_n26_transactions.

This lets you see patterns—like realizing that coffee purchases spiked in March compared to February. The ability to pull all account identifiers and balances via get_n26_accounts first ensures your AI client knows exactly which funds are contributing to any summary it generates later on, making the whole process airtight. You're not just getting data points; you're getting actionable financial intelligence.

Your agent doesn't wait for commands; it waits until you ask a specific question that requires synthesizing real-time balance checks with historical spending audits.