A
licenseNot graded
qualityD
maintenanceCryptographic proof of every AI decision. An immutable, verifiable audit trail MCP server.
1
MIT
dnnsec
by tudadada
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TDQS
B3.1/5.0
Scored across 2 tools
Disambiguation2/5
The two tools have overlapping purposes: both verify model integrity and check adversarial robustness, making it unclear when to use one versus the other. An agent would struggle to decide which tool handles a given security assessment request.
Naming Consistency4/5
Both tool names follow a consistent verb_noun pattern (verify_model_integrity, check_adversarial_robustness), though the verbs 'verify' and 'check' are near-synonyms, which slightly reduces clarity.
Tool Count2/5
With only two tools, the server feels thin for a domain as broad as neural network security. The count is at the extreme low end, offering minimal coverage for the stated purpose.
Completeness2/5
The tool surface is severely limited: it covers verification and robustness screening but lacks common operations like model hardening, attack generation, report generation, or remediation. The domain is not fully covered.
Maintenance
ActivityMaintained
ResponsivenessNo issues