NFT Log Analyser
mashishLABSCO SUMMARY
Two rules, and that is the point.
The thresholds shipped here are narrow — a memory ceiling and a view-count ceiling — and the value is in the shape rather than the coverage: a triage pass that says nothing when nothing is wrong. That is worth more in a performance workflow than a full metrics dump, because the dump is what you already have. Expect to edit the rules file to match your own app before it tells you anything useful.
What it is
A performance-triage server for mobile app monitoring data. You point it at a CSV of captured metrics and it applies rule-based checks, returning only the severe warnings rather than a full report — the design choice is deliberate, to keep the output from drowning the finding. The rules live in a file you can edit.
What you get
- Severe-problem detection over a performance data file you point it at by URL
- A physical memory warning when VmRSS goes over 1.3GB
- A Views-count warning when Views growth exceeds 700
- Output restricted to severe warnings, so nothing else competes for attention
- Rules editable in
.cursor/rules/quality-rules.mdcto match your own thresholds
Requirements
Python 3 and a checkout — create a virtualenv and pip install -r requirements.txt (package mcp-analyze-quality, version 0.1.0), then point your client at the venv's Python running main.py. No account and no key. It reads the data over HTTP, so the CSV has to be reachable: locally that means serving the directory, and for a team the README runs the server on a shared host with clients connecting over ssh.
Setup effort
Build from source — git clone git@github.com:DaSheng1994/mcp_analyze_quality.git
USE CASES
01
Triaging a performance capture after a test run
Hand it the CSV URL and read back only what crossed a threshold.
02
Catching a memory regression before release
Check whether resident memory went over the configured ceiling.
03
Sharing one analysis setup across a team
Run it on a shared host and have everyone's client connect to the same rules.
BEFORE YOU INSTALL
What to know first
Requires
- Python 3.8 or later
- The performance CSV reachable over HTTP (the README serves its folder with python3 -m http.server 8000)
Where it runs
Both documented setups run the server on your machine.
INSTALLATION
Connect your client
You clone this one yourself.
Server setup
TERMINAL
git clone git@github.com:DaSheng1994/mcp_analyze_quality.git
cd mcp_analyze_quality
python3 -m venv .venv
source .venv/bin/activate # Linux/macOS
pip install -r requirements.txtMCP Clients
Cursor
CURSOR · JSON
{
"mcpServers": {
"performance-analyzer": {
"command": "<YOUR_PATH_TO_PROJECT>/.venv/bin/python",
"args": [
"<YOUR_PATH_TO_PROJECT>/main.py"
],
"cwd": "<YOUR_PATH_TO_PROJECT>"
}
}
}Cursor — SSH
CURSOR — SSH · JSON
{
"mcpServers": {
"performance-analyzer": {
"command": "ssh",
"args": [
"<YOUR_SERVER>",
"cd <YOUR_PATH_TO_MCP_ANALYZE_QUALITY> && .venv/bin/python main.py"
],
"env": {}
}
}
}
