Shumei Anti-Fraud MCP. Scan media, text, and devices for risk instantly.

This server is built for your AI agent, giving it enterprise-grade risk assessment capabilities right out of the box. It lets you check text, images, audio clips, and device IDs against known fraud patterns instantly, letting you automatically filter spam or block traffic from suspicious sources before they ever hit your platform.

Text Abuse Detection with check_text_risk: You feed this tool a raw string of text, and it immediately returns a classification. This tells you if the content is abusive, how likely it is to be spam, or whether it contains restricted material. If the score crosses a certain threshold, you know exactly what action your agent needs to take—rejecting the input, flagging it for review, or just passing it through.

Image Screening with check_image_risk: You pass in an image URL or direct data stream, and the server scans it right away. It checks for NSFW material or any graphical elements that violate your platform's policy. This tool doesn't just say 'yes' or 'no'; it gives you a risk assessment of the visual content.

Audio Risk Prediction via check_audio_risk: When an uploaded audio file comes in, this function analyzes it to predict associated risks. It detects things like hate speech or copyrighted material usage, helping you filter out problematic media before your system processes it further. You get a risk score based on the content of the sound clip.

Device Fraud Validation with check_device_risk: If you receive an IP address or a unique Device ID, this tool runs checks against massive databases. It determines if that source is fraudulent, if it's using a VPN to mask its location, or if it originated from an emulator. This lets your agent block traffic from known bad actors and spoofing sources.

Your AI client doesn't need complex backend services to handle moderation; you just call the right tool. You can build logic that dictates action based on these immediate risk verdicts. For example, a user submits text (check_text_risk), then uploads an image (check_image_risk), and their device connects from a suspicious IP (check_device_risk).

Your agent runs all three checks in sequence. If any single check fails—say, the text is abusive or the device ID is flagged as a VPN—you can block the whole transaction immediately.

The server lets you perform live audits on user activity data. When your agent processes chat logs or large batches of submitted content, it doesn't just look at individual pieces; it gets an overall view of suspicious behavior across entire streams. This means you catch patterns of abuse, not just isolated incidents.

When setting up your workflow, you simply connect your AI client to this server and access the tools by name in your agent’s logic. You call check_text_risk for text inputs; you call check_image_risk for visuals; you call check_audio_risk for sound files; and you call check_device_risk whenever an IP or device identifier comes through.

Each tool provides a definitive, actionable risk score that dictates the next step: allow it, warn on it, or block it entirely.