io.github.luoshu-echorune/echorune-radar is an MCP server that live weather anywhere, with the radar drawn as text characters, not an image. Its tool list has not been published yet over http, requires no API key, and scores 59/100 on MCPpedia's security, maintenance and efficiency rubric.
Config is the same across clients - only the file and path differ.
{
"mcpServers": {
"io-github-luoshu-echorune-echorune-radar": {
"args": [
"-y",
"skills"
],
"command": "npx"
}
}
}Are you the author?
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Live weather anywhere, with the radar drawn as text characters, not an image.
Run this in your terminal to verify the server starts. Then let us know if it worked - your result helps other developers.
npx -y 'skills' 2>&1 | head -1 && echo "✓ Server started successfully"
After testing, let us know if it worked:
Five weighted categories - click any category to see the underlying evidence.
PYSEC-2021-856
Null Pointer Dereference vulnerability exists in numpy.sort in NumPy < and 1.19 in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays.
PYSEC-2021-857
Buffer overflow in the array_from_pyobj function of fortranobject.c in NumPy < 1.19, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values.
PYSEC-2021-854
A Buffer Overflow vulnerability exists in NumPy 1.9.x in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service.
PYSEC-2021-855
Incomplete string comparison in the numpy.core component in NumPy1.9.x, which allows attackers to fail the APIs via constructing specific string objects.
PYSEC-2019-108
** DISPUTED ** An issue was discovered in NumPy 1.16.0 and earlier. It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call. NOTE: third parties dispute this issue because it is a behavior that might have legitimate applications in (for example) loading serialized Python object arrays from trusted and authenticated sources.
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