A
licenseB
qualityA
maintenanceEnables AI agents to consume 50+ NVIDIA NIM models including LLMs, image generation, and vision through 10 MCP tools with rich metadata and advanced filtering.
11
358 npm
1
MIT
mcp-nvidia-nim
by luizGDpulz
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TDQS
C2.9/5.0
Scored across 11 tools
Disambiguation2/5
Half the tool set consists of explicit aliases (Portuguese names) that duplicate the English tools exactly, making it impossible to infer any selection difference. The six unique capabilities are distinct, but the aliases create multiple unclear boundaries and invite misselection.
Naming Consistency3/5
All names use a consistent nim_ prefix and snake_case, which is readable. However, the set mixes English and Portuguese conventions, and the alias pairs introduce duplicate naming patterns rather than a single predictable scheme.
Tool Count3/5
Eleven tools is a reasonable raw count, but five are redundant aliases, leaving only six unique capabilities. The aliases inflate the surface without adding functionality, making the count feel heavier than necessary.
Completeness4/5
The unique tools cover the core NIM lifecycle: status/quota inspection, general query, deep reasoning, code review, vision analysis, and document extraction. Minor gaps exist (e.g., no explicit model listing beyond status), but agents can work around them.
Maintenance
ActivityMaintained
ResponsivenessResponsive