AI agents have evolved from simple conversational tools into systems that manage spend, handle disputes, and execute payments from end to end. That evolution demands issuer processing infrastructure built to support AI-driven workflows across the entire payment stack.

Lithic's Authorization Intelligence brings programmable decisioning to card, 3DS, tokenization, and ACH. Our Model Context Protocol (MCP) server takes that a step further, making Lithic’s full platform accessible through a conversational AI interface.

AI tools are already able to search Lithic's documentation for troubleshooting guidance, API references, and code examples. The MCP server now enables AI agents to act on what they find using natural language, eliminating reliance on developer teams to update your card program’s strategies, analytics, and policies. 

With the Lithic MCP server, those same docs and examples become a live, actionable layer for creating, testing, and managing your card program in a single conversation.

Built for Every Team in Your Card Program

Card programs move fast, but engineering, risk, and product teams rarely move on the same timeline.

Developers optimize for integration speed and smooth build cycles, while risk and product teams need faster ways to validate and act on fraud patterns. The Lithic MCP server supports both by bringing live API access into the tools these teams already use.

Developers: Build and Test Without Leaving Your Editor

In the age of AI, developers are building differentiated card experiences, agentic commerce products, and new payment workflows. Shipping those products typically means working with a payments API, which can mean rotating between editors, documentation, and testing environments. That constant context switching slows teams down and makes integrations harder to maintain. With the Lithic MCP server, your AI assistant can work directly with the live Lithic API as you build.

Your AI assistant can:

• Pull up documentation, API references, and code examples on demand without opening a browser
• Inspect request and response schemas for any endpoint in the Lithic API
• Generate integration code informed by live API context instead of outdated training data
• Execute sandbox API requests directly within the conversation

For sandbox testing, connecting a Sandbox API key unlocks Lithic’s simulation layer. You can validate an entire authorization flow using natural language.

In a single conversation, you can:

• Create a virtual card and assign it to a test account
• Configure Authorization Rules controlling merchant categories, transaction limits, and velocity
• Run transactions against those rules to confirm they’re performing as intended
• Simulate authorization challenges to verify your cardholder authentication flows
• Review authorization responses, update the configuration, and run it again on the spot

Iteration that once depended on tickets and deployment windows can now happen in one continuous loop between configuration and validation.

Risk and Product Teams: Close the Gap Between Insight and Action

Risk and product teams work closely together to update and deploy program fraud rules, and that relationship starts long before production. Risk analysts require hands-on training, which ideally happens in dedicated training environments. But waiting for engineering teams to build testing scenarios extends the onboarding timeline, compelling analysts instead to train on live cases, where any unintended changes made during the learning process can open your program up to financial and regulatory risks.

With Lithic’s MPC server, risk teams no longer need to rely on developers to create training environments. Because it connects to Lithic's sandbox API through the editors and chat interfaces your team already uses, a risk ops lead can describe the scenarios they need and let the AI assistant configure the rest.

An effective use case for this training is transaction monitoring, which will be available to Lithic clients later this quarter. Transaction monitoring assistants will let teams define tagging rules based on risk scores and transaction attributes, then route flagged transactions into a case manager for human review.

A transaction monitoring training setup flow in the sandbox might look like this:

• Describe the monitoring scenarios your team needs to practice, then let the AI assistant pull the relevant rule schemas from Lithic's documentation
• Instruct the agent to configure tagging rules that flag transactions based on the risk signals your analysts need to recognize
• Set up case creation rules that route flagged transactions into the case manager queue
• Simulate a batch of transactions that includes both suspicious patterns and legitimate activity to confirm the rules behave as expected
• Review the resulting case queue with new analysts, then adjust rules and re-simulate until the training environment matches your production patterns

Traditionally, setting up a training queue like this can take weeks of coordination between risk and engineering. The Lithic MCP server streamlines it into a single sandbox session, owned by the team that understands the monitoring logic best.

Simple to Connect, Ready to Use

The Lithic MCP server plugs into the MCP support already built into many AI-aware editors and assistants, so you can be up and running quickly.

To connect the Lithic MCP server to your environment:

1. Add the Lithic MCP server URL to your editor’s MCP configuration
2. Verify that you can search Lithic documentation and explore API endpoints with no API key
3. Store your Lithic API key in a .env file at your project root, and add .env to .gitignore so your assistant can execute requests without exposing secrets
4. Optional: Add a short custom instruction that tells your AI assistant when to use the Lithic MCP tools and where to find the API key

To keep teams in their existing tools and reduce context switching, the Lithic MCP server works with Cursor, Claude Code, VS Code with GitHub Copilot, Windsurf, Cline, Claude Desktop, Claude.ai, ChatGPT, and JetBrains IDEs. 

As agentic commerce evolves, card programs need infrastructure built for decisioning that can change as fast as the agents using it. Lithic’s MCP server and Intelligent Authorization position card programs to own this new operating model, where authorization becomes programmable, adaptive, and ready for agentic payments.

Getting Started

The Lithic MCP server brings AI-native workflows into the tools your card program teams already use every day. Getting connected takes minutes, and Lithic provides editor-specific setup guides and reference documentation to minimize overhead from the start.

Ready to bring AI agents into your card program workflows? Explore the Lithic MCP server or reach out to our team to get started.