$ loading_
Monitor LLM cost, errors, latency, alerts, and evaluations from AI coding tools.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "com.argosvix/server" MCP server from askskill: Run: claude mcp add 'com-argosvix-server' -- npx -y @argosvix/mcp-server
No documentation provided
Check the source repo for usage and examples.
Add observability to Python MCP servers and monitor latency, errors, and usage.
Monitor observability issues and auto-fix service errors and billing pipeline problems.
Run end-to-end browser testing and quality debugging directly from your IDE.
Query LLM observability data via MCP to diagnose performance and issues.
Track AI usage, costs, logs, and debug model interactions across apps.
Compare AI models, estimate costs, and generate production-ready code in your IDE.