MCP server · source category: Monitoring
argosvix/mcp-server
Observability for AI agents: LLM cost, errors and latency across OpenAI, Anthropic, Gemini and Mistral, plus alerts, budge…
Observability for AI agents: LLM cost, errors and latency across OpenAI, Anthropic, Gemini and Mistral, plus alerts, budget gates, evals and safety checks.
Record
- Type
- MCP server
- Category
- Analytics & Monitoring
- Authentication
- No authentication
- Pricing
- Free
- Documentation
- https://github.com/argosvix/mcp-server
- Repository
- https://github.com/argosvix/mcp-server
Fields are reproduced from the source registry as-is. “Unknown” means the source did not describe the field — it is not an inference. See the methodology for how records are collected and normalised.
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