Honeypot MCP Server

The Honeypot MCP Server is a purpose‑built transaction intelligence platform that leverages the Model Context Protocol to expose a rich set of tools for monitoring, analyzing, and managing fraudulent card activity. Its core purpose is to create a controlled environment where AI agents can act as vulnerable elderly personas, deliberately handing out virtual card details to scammers. By capturing the ensuing transactions through a secure integration with Lithic’s Virtual Card Platform, the server gathers actionable intelligence on scammer tactics, merchant interactions, and transaction patterns.

For developers building AI‑driven security or fraud‑detection solutions, this server removes the friction of setting up complex payment‑card monitoring infrastructure. Instead of writing custom webhook handlers or parsing raw transaction logs, an AI assistant can call high‑level tools such as or over MCP, receiving structured data ready for analysis. The 13‑tool suite covers everything from card lifecycle management to real‑time feed subscription, enabling end‑to‑end workflows that span creation, monitoring, and response.

Key capabilities include:

• Card Management – Create, list, update limits, and toggle the state of honeypot cards via Lithic API calls.
• Transaction Intelligence – Retrieve individual transactions, perform filtered searches, and aggregate data by merchant or card.
• Real‑Time Monitoring – Subscribe to alerts and consume a live transaction feed, allowing an AI agent to react instantly to suspicious activity.
• Health and Governance – A dedicated tool ensures the server remains operational, while the MCP transport layer supports both HTTP and Stdio for flexible deployment.

Typical use cases span academic research, threat‑intel platforms, and compliance teams. A researcher can program an AI persona to interact with scammers, then use the server’s tools to collect a dataset of fraudulent transactions for machine‑learning models. A security operations center can integrate the server into its SOC workflow, automatically flagging and triaging high‑risk transactions without manual intervention.

What sets this MCP server apart is its seamless integration with the Model Context Protocol. By exposing tools as first‑class MCP capabilities, it allows any MCP‑compliant client—whether a Claude assistant or a custom Python bot—to orchestrate complex fraud‑detection logic in a declarative, type‑safe manner. This removes the need for bespoke SDKs or HTTP wrappers and ensures that AI assistants can focus on intelligence gathering rather than plumbing.