A
licenseNot graded
qualityC
maintenanceEnables AI agents to access observability and evaluation data, including run history, span traces, LLM-as-judge evaluation results, and regression reports.
MIT
@argosvix/mcp-server
by argosvix
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TDQS
A4.2/5.0
Scored across 87 tools
Disambiguation5/5
Every tool has a clearly distinct purpose. For example, there are multiple alert-related tools (acknowledge_alert, auto_silence_noisy_alert, silence_alert, etc.) but each targets a unique action like acknowledging a single event, bulk-silencing, or muting. Descriptions are detailed enough to avoid ambiguity.
Naming Consistency5/5
All 87 tool names follow a consistent verb_noun pattern in snake_case (e.g., create_alert, list_alerts, delete_alert). Verbs like get, list, create, update, delete, propose, etc. are used uniformly, making naming predictable.
Tool Count3/5
With 87 tools, the count is very high and exceeds typical well-scoped ranges (3-15). However, the server covers a broad domain (calls, alerts, budgets, evaluations, prompts, projects, etc.) as a comprehensive admin interface, so the count is somewhat justified but still feels heavy.
Completeness5/5
The tool set covers core CRUD/lifecycle operations for each subdomain (alerts, calls, eval, prompts, webhooks, budgets, policies, projects). There are no obvious gaps; even advanced operations like automated silencing, proposal reply, and approval request are included.
Maintenance
ActivityStale
ResponsivenessNo recent community issues