F
licenseA
qualityD
maintenanceEnables autonomous prompt improvement for voice AI agents through feedback analysis, test generation, and iterative testing.
10
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standard-vocal-mcp
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TDQS
A3.6/5.0
Scored across 6 tools
Disambiguation5/5
Each tool targets a distinct responsibility: listing, deploying, evaluating, analyzing audio, diffing prompts, and gating regressions. Even run_eval and regression_gate are clearly separated, with the former generating scores and the latter comparing against a baseline.
Naming Consistency2/5
The first three tools follow a verb_noun pattern (list_agents, deploy_agent, run_eval), while the last three are noun-centric (audio_forensics, prompt_diff, regression_gate). This split in grammatical structure makes the naming convention inconsistent and harder to predict.
Tool Count5/5
Six tools is well-scoped for a specialized server focused on voice agent lifecycle and evaluation. Every tool earns its place, and the count is neither too small nor bloated.
Completeness4/5
The set covers the core workflow: discover agents, deploy new ones, run tests, analyze call audio, version prompts, and gate updates. Minor gaps include no delete_agent or direct update_agent, but these are not critical for the server's apparent purpose.
Maintenance
ActivitySlowing
ResponsivenessNo issues