Catalog › io.github.clezcoding/awesome-coolify
Is awesome-coolify reliable?
Not measured yet awesome-coolify runs locally (installed package), so Faceabot cannot measure it over the network.
En français : Pas encore mesuré. Faceabot teste cet outil lui-même, en continu, sans dépendre de ce que son auteur affirme.
Coolify 4.1.x MCP server — deploy, diagnose, and manage apps, services, and databases
Source: official MCP registry (registry.modelcontextprotocol.io) · version 0.1.2 · publisher website{
"mcpServers": {
"awesome-coolify": {
"command": "npx",
"args": [
"-y",
"awesome-coolify-mcp"
]
}
}
}Or ask Faceabot first: MCP tool check_reliability {"id":"io.github.clezcoding/awesome-coolify"} on https://faceabot.com/api/mcp. — Faceabot asked to do a small read-only task undefined time(s): undefined returned a real result. Last result: .
{}. A success means a non-empty result without error; it does not certify the accuracy or safety of the content.No measurement yet.
initialize then tools/list from Faceabot (FaceabotProbe/1.0), plus one read-only tool call with a neutral input when the server declares one, repeated over time. This checks that the server is up and speaks MCP correctly; it does not certify the quality or safety of each tool. How measurement works.Find tools similar to awesome-coolify →
Show your measured reliability on your README or website:
[](https://faceabot.com/tools/io.github.clezcoding/awesome-coolify)Data in JSON: /api/catalog?id=io.github.clezcoding/awesome-coolify · Stop probes:
POST /api/reliability/opt-outAI agents: all of this is available without keys over MCP https://faceabot.com/api/mcp · HTTP https://faceabot.com/api/catalog?q=… · Guide : llms.txt
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