GoCardless has launched a Model Context Protocol tool, enabling developers and merchants to interact with its platform using natural language via an LLM.
Following this announcement, GoCardless has introduced a Model Context Protocol (MCP) tool that allows developers and merchants to communicate with its bank payment platform through natural language, using their preferred large language model (LLM). The move is intended to reduce integration complexity and surface payment data more quickly for businesses of varying technical backgrounds.
From integration to intelligence
According to the official press release, the MCP tool supports two primary use cases. First, it allows ecommerce partners to describe their payment requirements to an LLM and receive tailored implementation guidance alongside ready-to-use code, removing the need for detailed knowledge of bank payment protocols. Second, it enables merchants to query live payment data directly through natural language. A business operator could, for example, ask how many payments are overdue on a given day and receive an immediate response drawn from their GoCardless data.
By lowering the technical barrier to integration, the tool is positioned to shorten the time between a merchant deciding to adopt GoCardless and going live on their platform.
Agentic commerce as a longer-term objective
Beyond current developer workflows, GoCardless describes the MCP as a technical foundation for what it terms 'agentic commerce' — a model in which AI systems move beyond responding to queries and begin making independent decisions. The protocol is designed to allow such agents to interact with the GoCardless platform securely and autonomously as that capability matures.
The launch fits within a broader pattern of AI and machine learning investment at GoCardless. The company has previously developed Success+, a tool that optimises payment retry logic and recovers, on average, 70% of initially failed payments, and Protect+, a fraud prevention tool that identifies and blocks high-risk transactions before they are processed.
The MCP launch represents a shift in how payments infrastructure can be accessed — moving from code-first developer documentation toward conversational interfaces layered on top of existing APIs. As LLM adoption grows among developers and non-technical business users alike, payment platforms that expose their functionality through standardised protocols stand to reduce onboarding friction and expand their addressable user base.
