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Is glimind reliable?

Being measured Measurement in progress: 2 check(s) so far. A verdict needs at least 3 checks.

Last check: 2026-10-19 15:31 UTC · answered in 10501 ms · remote (no install)

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Picked from Faceabot's live measurements. Or let Faceabot choose: GET https://faceabot.com/resolve?need=…

En français : Mesure en cours. Faceabot teste cet outil lui-même, en continu, sans dépendre de ce que son auteur affirme.

What it does

Live reliability for AI agent tools: is it working right now, and how do I call it correctly?

Source: official MCP registry (registry.modelcontextprotocol.io) · version 0.1.0 · publisher website
Connect your agent
{
  "mcpServers": {
    "glimind": {
      "url": "https://glimind.com/mcp"
    }
  }
}
Or ask Faceabot first: MCP tool check_reliability {"id":"io.github.shawndei/glimind"} on https://faceabot.com/api/mcp.
Does it actually do the job?

Real task being tested — Faceabot asked list_breakages to do a small read-only task 2 time(s): 2 returned a real result, the last 2 in a row. Last result: ok in 3694 ms.

Sample input: {}. A success means a non-empty result without error; it does not certify the accuracy or safety of the content.
Faceabot measurements
WhenAnswersReal taskLatency
2026-10-19 15:31 UTC✅ ok✅ done10501 ms
2026-10-19 00:25 UTC✅ ok✅ done8501 ms
Method: MCP 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.

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Publisher of glimind?

Show your measured reliability on your README or website:

Faceabot reliability badge for glimind

[![Measured by Faceabot](https://faceabot.com/badge/io.github.shawndei/glimind.svg)](https://faceabot.com/tools/io.github.shawndei/glimind)
Data in JSON: /api/catalog?id=io.github.shawndei/glimind · Stop probes: POST /api/reliability/opt-out

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