A
licenseNot graded
qualityD
maintenanceEnables lightning-fast inference using Groq models through MCP clients, supporting vision, speech, batch processing, and agentic tasks.
MIT
Groq MCP Server
by AyrtonFelipe
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TDQS
B3.1/5.0
Scored across 4 tools
Disambiguation5/5
Each tool has a clearly distinct purpose targeting different Groq service capabilities: audio transcription, batch processing, text completion, and vision analysis. There is no overlap or ambiguity in their functions, making it easy for an agent to select the appropriate tool.
Naming Consistency5/5
All tool names follow a consistent 'groq_' prefix with descriptive snake_case suffixes (e.g., groq_audio_transcription, groq_batch_processing). This uniform pattern enhances predictability and readability across the tool set.
Tool Count4/5
With 4 tools, the count is reasonable for a Groq API server, covering core functionalities like text, audio, vision, and batch processing. It is slightly lean but well-scoped, as each tool serves a distinct purpose without redundancy.
Completeness4/5
The tool set covers key Groq model types (text, audio, vision) and includes batch processing for efficiency, which addresses common use cases. A minor gap might be the lack of specific tools for model management or configuration, but the surface is largely complete for typical inference tasks.
Maintenance
ActivityInactive
ResponsivenessNo issues