retail-anomaly-detection (percy-han/retail-anomaly-detection) is an MCP server listed on the M8ven Trust Index. M8ven has not graded it yet. No publisher has claimed this listing.

Back to MCP Trust IndexM8ven
C
Emerging
74/100

retail-anomaly-detection

GCP 电商销量异常检测与多模态根因调查系统 — BQML ARIMA_PLUS + Vertex AI Agent Engine (Gemini) + Cloud SQL + Cloud Run 看板

→ percy-han/retail-anomaly-detection· listed on github_repo_search

Emerging. No concerning findings. Grades remain capped until the project builds reputation through adoption. Grades reflect the full trust pyramid: code, verification depth, and reputation. New projects cap at C until adoption is earned.

How we verified

⚡ Live Monitored: not connected

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Who stands behind it

percy-han

Source: github_repo_search

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Install from

GitHub

The grade above is for the source repository. Registries can serve a different version, so we mark the ones we were not able to read.

// key findings
✅
No credential exfiltration, no sensitive file access, no obfuscation
Static analysis found nothing flowing your secrets to unexpected places.
✅
Open source with a license and README
Anyone can audit the code, the license is declared, and the publisher documents what it does.
🔐
You'll be asked for 1 credential: DB_PASSWORD
These are read from process.env at runtime. Make sure you trust where they’ll be sent.
// environment variables
To run this server yourself, you supply these values. They go in your own MCP client configuration and stay on your machine. The secret label means the value is sensitive, not that the server mishandles it.
configDB_HOSTCloud SQL 私有 IP
configDB_NAME
configDB_USER
🔐 secretDB_PASSWORD
configDB_PORT
configCACHE_TTL_SECONDS
configGOOGLE_CLOUD_PROJECTstudy-project-496907
configMODEL_LOCATION
configGOOGLE_CLOUD_LOCATION需要 GOOGLE_GENAI_USE_VERTEXAI=TRUE + =global；
configPRIMARY_MODEL
configFALLBACK_MODEL
configMAX_IMAGES_PER_BATCH
configMAX_IMAGES_PER_REVIEW
configMAX_REVIEWS
configTEST_ASIN
configTEST_START
configTEST_END
configBQ_MCP_URL
configBQ_MCP_PROJECT
configAGENT_ENGINE_LOCATION
configREVIEWS_TABLE<project>.amazon_reco.Amazon_Fashion
configINVENTORY_TABLE<project>.amazon_reco.product_inventory
configGCP_PROJECT_ID
configBQ_DATASET
configBQ_ANOMALY_TABLE
configLOOKBACK_HOURS
configPUBSUB_TOPIC_INVESTIGATION
configAGENT_ENGINE_RESOURCE_NAMEprojects/.../locations/us-central1/reasoningEngines/...
Deployment configuration, supplied by whoever hosts the server. Users are not asked for these.
deployPORT
// quality suggestions

Tests exist

No test files found

Add tests that exercise each declared tool.

Claim the listing to review these findings one by one and send us a correction where you disagree, straight to the team. Claiming also means we tell you when the grade moves, and reach you first if we find anything urgent.

// full audit trail
The findings above are the summary. The full trail, every check we ran, each deduction, the network hosts observed and the dependency advisories, goes to verified publishers, along with an alert whenever a new one lands. Verified publishers can also review each finding and dispute it in one click. Publisher corrections have sharpened several of our checks this month, because the maintainer knows the codebase better than any scanner.
// improvement guidance — verified publishers only
We have 1 concrete improvement we can share with the publisher of this MCP. Each comes with specific guidance to raise the trust score.
// embed badge in your README
[![M8ven Score](https://m8ven.ai/badge/mcp/percy-han/retail-anomaly-detection)](https://m8ven.ai/mcp/percy-han/retail-anomaly-detection)
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commit: feb95188fd3f21b810163b7a040d9a33ae7f233a
code hash: 39956367f817a722fc43f6e45f30b5051141f0e242d8f18cc4245054870ce70c
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