A
licenseA
qualityB
maintenanceMCP server for Arize Phoenix enabling AI agents to perform LLM tracing, evaluation, and dataset management for automated quality assurance.
8
MIT
@arizeai/phoenix-mcp
Officialby Arize-ai
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TDQS
B3.2/5.0
Scored across 27 tools
Disambiguation3/5
Multiple tools for fetching prompts (get-prompt-by-identifier, get-prompt, get-latest-prompt) have overlapping functionality, which could cause confusion. Other tools are distinct.
Naming Consistency4/5
Tool names follow a consistent verb-noun pattern with hyphens (e.g., list-prompts, get-dataset). Minor deviations like get-latest-prompt vs get-prompt are present but overall consistent.
Tool Count4/5
27 tools cover multiple domains (prompts, datasets, experiments, traces, etc.) and are justified given the breadth of functionality, though slightly on the high side.
Completeness3/5
The tool surface covers core operations for prompts, datasets, and observability, but lacks delete operations for prompts and datasets, and does not include create dataset or project.
Maintenance
ActivityActive
ResponsivenessWithin a week