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AEGIS Governance

Quantitative governance gate for AI agents. Six gates (risk, profit, novelty, complexity, quality, utility) return PROCEED/PAUSE/HALT/ESCALATE with confidence scores and hash-chained, tamper-evident a…

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▣ Score BreakdownMCPScore = Σ(raw × weight)

DimensionRawWeighted

Security

35%

0.0

Freshness

25%

0.0

Adoption

20%

0.0

Quality

10%

0.0

Trust

10%

0.0

Total

0.0

⚙ Install config

Source-only — no published npm / pypi package detected.
Clone and follow the build instructions in the repo: github.com/undercurrentai/aegis-mcp

⛁ Raw data

weekly downloads0

github stars0

forks0

open issues0

license✗ missing

readme length0 chars

last updated4h ago

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