Pagos, an all-in-one provider of payments optimization solutions, today announces the launch of its first Model Context Protocol (MCP) Server, making it easier than ever for AI agents and applications to query the payments intelligence available only through Pagos.
This MCP Server, designed for their direct-to-network BIN data solution, allows large language models (LLMs) and AI-powered tools to securely query real-time BIN-level card data directly from card networks. This marks the company’s first step toward a more open, accessible future for payment data!
Seamlessly Integrate BIN Data into Your Workflows
In this first release, the Pagos MCP Server exposes the BIN-level card data merchants need to efficiently manage card-based payments globally. Developers and businesses can now plug this data directly into their AI workflows, making it easier than ever to:
- Get to know your customer base with card details like issuer, card brand, and country data
- Design routing strategies around preferable approval rates and processing costs
- Finetune your retry strategy
- Create BIN-based fraud rules to identify and block issuing banks or specific BINs frequently associated with fraud or carding attacks
- Reduce your interchange costs by identifying when a customer’s card qualifies for Level II or III data
- Prototype AI tools without building a custom connector to Pagos
“We’re watching merchants embrace AI as a partner in their quest for payments optimization,” said Klas Bäck, CEO and Co-founder of Pagos. “But these tools are only as good as the context they can access. Our MCP Server opens the door to smarter BIN-based automation by giving AI agents the most up-to-date data directly from the card networks.”
Get Started in Minutes
To level-up your BIN data usage:
- Explore the Pagos MCP Server on GitHub
- Sign up for Pagos to get API access
- Deploy the server locally or in your environment of choice
Pagos plans to expand its MCP offerings over the coming months, adding support for other core products and workflows. In the meantime, they’re actively seeking feedback from developers, merchants, and AI builders.
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