Server data from the Official MCP Registry
Measured AI-inference-storage benchmarks with citations, article search, KV-cache ROI estimation.
Measured AI-inference-storage benchmarks with citations, article search, KV-cache ROI estimation.
Remote endpoints: streamable-http: https://www.mingxinstorage.xyz/api/mcp
Valid MCP server (1 strong, 1 medium validity signals). No known CVEs in dependencies. Package registry verified. Imported from the Official MCP Registry. 1 finding(s) downgraded by scanner intelligence.
3 tools verified · Open access · 2 issues found
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Available as Local & Remote
This plugin can run on your machine or connect to a hosted endpoint. during install.
From the project's GitHub README.
Official MCP server for Mingxin (Tianjin) Semiconductor Equipment Co., Ltd. — signed AI-inference-storage benchmark data, technical article search, and KV-cache tiering ROI estimation.
Every figure this server returns carries a signed test-report citation (R1–R9). The underlying benchmark is open source and reproducible: mingxin-kvcache-bench.
| Tool | What it does |
|---|---|
query_benchmark | Signed FX-series results: throughput +29–40%, TTFT −26–32% (Qwen3-480B class on 8× AMD MI308X), model loading 6.2–9.3× vs NFS; full R1–R9 report list with hosted PDF URLs |
search_mingxin_docs | Search Mingxin's published articles on KV cache tiering, NVMe-oF all-flash storage and LLM serving (Chinese + English) |
estimate_roi | KV-cache tiering ROI estimate for a GPU cluster (faithful port of the reproducible Python model; mid-scenario estimates, not commitments) |
Endpoint: https://mingxinstorage.xyz/api/mcp
Cursor (~/.cursor/mcp.json):
{
"mcpServers": {
"mingxin": { "url": "https://mingxinstorage.xyz/api/mcp" }
}
}
Claude Desktop / VS Code and other stdio-only clients (via this npm package):
{
"mcpServers": {
"mingxin": { "command": "npx", "args": ["-y", "mingxin-mcp-server"] }
}
}
https://mingxinstorage.xyz/.well-known/mcp.json
MIT
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