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Is mcp reliable?

Being measured Measurement in progress: 1 check(s) so far. A verdict needs at least 3 checks.

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

What it does

Research-backed linting + generation for agent context files (CLAUDE.md, AGENTS.md, Cursor rules).

Source: official MCP registry (registry.modelcontextprotocol.io) · version 1.1.0 · publisher website
Connect your agent
{
  "mcpServers": {
    "mcp": {
      "url": "https://mcp.promptarch.ai/mcp"
    }
  }
}
Or ask Faceabot first: MCP tool check_reliability {"id":"ai.promptarch/mcp"} on https://faceabot.com/api/mcp.
Does it actually do the job?

Not tested with a real task yet. Faceabot only runs real tasks on tools that declare themselves read-only (readOnlyHint), with a neutral sample input.

Faceabot measurements
WhenAnswersReal taskLatency
2026-10-06 09:30 UTC✅ ok4961 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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specpack Not measured yet

Audit and write CLAUDE.md / AGENTS.md / Cursor rules; generate full build specs for new projects.

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Publisher of mcp?

Show your measured reliability on your README or website:

Faceabot reliability badge for mcp

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

AI 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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