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Add igorolv/loki-mcp-server to Monitoring

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@@ -3173,6 +3173,7 @@ Access and analyze application monitoring data. Enables AI models to review erro
- [pydantic/logfire-mcp](https://github.com/pydantic/logfire-mcp) 🎖️ 🐍 ☁️ - Access OpenTelemetry traces and metrics through Logfire. - [pydantic/logfire-mcp](https://github.com/pydantic/logfire-mcp) 🎖️ 🐍 ☁️ - Access OpenTelemetry traces and metrics through Logfire.
- [Higangssh/homebutler](https://github.com/Higangssh/homebutler) [![homebutler MCP server](https://glama.ai/mcp/servers/Higangssh/homebutler/badges/score.svg)](https://glama.ai/mcp/servers/Higangssh/homebutler) 🏎️ 🏠 - Homelab management across multiple servers via SSH: system resource monitoring, Docker containers, Wake-on-LAN, network scans, open-port checks and alerts. - [Higangssh/homebutler](https://github.com/Higangssh/homebutler) [![homebutler MCP server](https://glama.ai/mcp/servers/Higangssh/homebutler/badges/score.svg)](https://glama.ai/mcp/servers/Higangssh/homebutler) 🏎️ 🏠 - Homelab management across multiple servers via SSH: system resource monitoring, Docker containers, Wake-on-LAN, network scans, open-port checks and alerts.
- [incu6us/loki-mcp-server](https://github.com/incu6us/loki-mcp-server) [![incu6us/loki-mcp-server MCP server](https://glama.ai/mcp/servers/incu6us/loki-mcp-server/badges/score.svg)](https://glama.ai/mcp/servers/incu6us/loki-mcp-server) 🏎️ 🏠 🍎 🪟 🐧 - Query Grafana Loki directly with a discovery-first workflow: labels, values, series and LogQL queries, without requiring Grafana. - [incu6us/loki-mcp-server](https://github.com/incu6us/loki-mcp-server) [![incu6us/loki-mcp-server MCP server](https://glama.ai/mcp/servers/incu6us/loki-mcp-server/badges/score.svg)](https://glama.ai/mcp/servers/incu6us/loki-mcp-server) 🏎️ 🏠 🍎 🪟 🐧 - Query Grafana Loki directly with a discovery-first workflow: labels, values, series and LogQL queries, without requiring Grafana.
- [igorolv/loki-mcp-server](https://github.com/igorolv/loki-mcp-server) [![igorolv/loki-mcp-server MCP server](https://glama.ai/mcp/servers/igorolv/loki-mcp-server/badges/score.svg)](https://glama.ai/mcp/servers/igorolv/loki-mcp-server) ☕ 🏠 🍎 🪟 🐧 - Read-only Grafana Loki (2.6.1 and 3.x) for agents: label and stream discovery, bounded LogQL pages, counts by label or time bucket, and log export; several stands per server.
- [rbmuller/scherlok](https://github.com/rbmuller/scherlok) [![rbmuller/scherlok MCP server](https://glama.ai/mcp/servers/rbmuller/scherlok/badges/score.svg)](https://glama.ai/mcp/servers/rbmuller/scherlok) 🐍 🏠 🍎 🪟 🐧 - Read-only data quality monitoring for Postgres, BigQuery, Snowflake, MySQL and DuckDB: warehouse profiling, anomaly detection and optional dbt lineage. - [rbmuller/scherlok](https://github.com/rbmuller/scherlok) [![rbmuller/scherlok MCP server](https://glama.ai/mcp/servers/rbmuller/scherlok/badges/score.svg)](https://glama.ai/mcp/servers/rbmuller/scherlok) 🐍 🏠 🍎 🪟 🐧 - Read-only data quality monitoring for Postgres, BigQuery, Snowflake, MySQL and DuckDB: warehouse profiling, anomaly detection and optional dbt lineage.
- [seekrays/mcp-monitor](https://github.com/seekrays/mcp-monitor) 🏎️ 🏠 - Real-time system metrics: CPU, memory, disk, network, host and process information. - [seekrays/mcp-monitor](https://github.com/seekrays/mcp-monitor) 🏎️ 🏠 - Real-time system metrics: CPU, memory, disk, network, host and process information.
- [spanlens/Spanlens](https://github.com/spanlens/Spanlens/tree/main/packages/mcp-server) [![spanlens/Spanlens MCP server](https://glama.ai/mcp/servers/spanlens/Spanlens/badges/score.svg)](https://glama.ai/mcp/servers/spanlens/Spanlens) 🎖️ 📇 ☁️ - Read-only access to Spanlens LLM observability: request logs, costs, agent traces, anomalies, model savings and per-user analytics. - [spanlens/Spanlens](https://github.com/spanlens/Spanlens/tree/main/packages/mcp-server) [![spanlens/Spanlens MCP server](https://glama.ai/mcp/servers/spanlens/Spanlens/badges/score.svg)](https://glama.ai/mcp/servers/spanlens/Spanlens) 🎖️ 📇 ☁️ - Read-only access to Spanlens LLM observability: request logs, costs, agent traces, anomalies, model savings and per-user analytics.