GoCardless introduces Al-native tool for businesses to communicate with the platform in natural language

LONDON UK, 18 FEBRUARY 2026 – Bank payment company GoCardless has announced the launch of its Model Context Protocol (MCP), a tool enabling developers to use their preferred Large Language Model (LLM) to ‘speak’ to GoCardless.

By using natural language to communicate with the platform, merchants can get instant answers, surface payment information, and significantly reduce the time it takes to integrate GoCardless into their website or platform.

Indicative use cases:

• Streamlined Integration: An e-commerce partner can describe their specific payment requirements to an LLM to receive tailored implementation guidance and ready-to-use code -- allowing them to integrate GoCardless without needing to master the complexities of bank payment protocols.

• Instant Business Intelligence: A gym owner can use natural language to query their GoCardless data via an LLM, asking for real-time insights such as, "How many payments are overdue today?".

While the MCP immediately simplifies developer workflows today, it also serves as the technical foundation for agentic commerce in the future. As AI evolves from simple assistants to ‘agents’ capable of making independent decisions, the MCP ensures these agents can interact with GoCardless securely and autonomously.

Shaun Puckrin, Chief Product Officer at GoCardless, said: “We’re excited to launch our MCP, a move which dramatically simplifies how users can communicate with the GoCardless platform. We’re meeting merchants where they are and, with AI as a co-pilot, making it even easier for them to move from idea to execution.”

This news is the latest milestone in GoCardless’ innovative history. The company has a long track record of leveraging machine learning — another subset of AI — and the millions of transactions it processes each year to solve complex payment challenges. This includes the development of Success+ to optimise payment retries which recovers, on average, 70% of payments that initially fail, and Protect+, an intelligent fraud prevention tool that proactively identifies and blocks high-risk transactions.