Qonto MCP Server

The Qonto Local MCP Server is a bridge that lets AI assistants, such as Claude, tap directly into a business’s banking and financial operations. By exposing Qonto’s API through the Model Context Protocol, developers can give their AI tools the ability to read account balances, initiate transfers, and retrieve transaction histories—all within a single conversational flow. This removes the friction of switching between separate apps or writing custom integrations for each use case.

For developers, the server offers a streamlined path to embed financial intelligence into customer support bots, budgeting assistants, or internal analytics dashboards. Instead of building bespoke connectors for every new financial service, the MCP server presents a unified set of resources and tools that the AI can call on demand. This reduces boilerplate code, speeds up prototyping, and ensures that sensitive financial data is handled in a consistent, auditable manner.

Key capabilities include:

• Secure API access – the server authenticates using a Qonto API key and organization ID, keeping credentials out of client code.
• Rich resource exposure – account summaries, transaction lists, and transfer endpoints are available as typed resources that the AI can query or mutate.
• Prompt‑level context – by integrating with Claude Desktop, the server can inject contextual data (e.g., recent statements) into prompts so that responses are grounded in real‑time financial facts.
• Transport flexibility – the server supports both standard stdio and streamable‑HTTP transports, allowing it to run as a lightweight Docker container or a local process.

Typical use cases span customer‑facing chatbots that can verify balances, internal finance teams automating reconciliation tasks, or compliance tools that flag suspicious activity in real time. Because the MCP server translates API calls into simple function‑like requests, developers can focus on higher‑level logic rather than handling authentication or rate limits.

What sets the Qonto MCP Server apart is its emphasis on security and trust. The README explicitly warns about potential risks of malicious servers, encouraging teams to audit the MCP implementation before deployment. By combining a well‑defined protocol with clear documentation and Docker support, it offers a reliable foundation for building AI‑powered financial workflows that respect both privacy and operational integrity.