Provides Claude with read-only access to PC diagnostics including hardware specs, live performance metrics, disk usage, network checks, and more, enabling natural language queries about PC health and performance.
A read-only MCP server for the Logitech Sync Cloud API, providing tools to inspect rooms, desks, devices, health, occupancy, coverage, environmental readings, and network information.
Enables Claude to discover and understand infrastructure-as-code drift by listing projects with drift, analyzing Terraform plan outputs, and providing remediation information.
Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.
A lightweight server that provides real-time system information including CPU, memory, disk, and GPU statistics for monitoring and diagnostic purposes.
Enables Claude to interact with Karma Alert dashboard to monitor and analyze Kubernetes alerts. Provides tools to check alert status, filter by cluster/severity, get detailed alert information, and analyze alert statistics and trends.
Enables interaction with Blacksmith CI analytics to query workflow runs, jobs, test results, and usage metrics. It provides detailed access to CI/CD data including job logs and billing information directly through Claude.
Enables interaction with Google Cloud Platform services through gcloud CLI, supporting operations like querying logs, checking Cloud Run status, managing secrets, executing Cloud SQL queries, and monitoring billing information.
The AgentOps MCP server provides access to observability and tracing data for debugging complex AI agent runs. This adds crucial context about where the AI agent succeeds or fails.
A Model Context Protocol server that connects to AppSignal, allowing users to fetch, list, and analyze incident information from their AppSignal monitoring.
A Model Context Protocol server that provides AI agents with controlled read access to Datalust Seq instances for log analysis and monitoring. It enables agents to search events, execute data queries, and retrieve information about signals, dashboards, and alerts.
Enables AI agents to interact with the Honeybadger error monitoring service to list, filter, and analyze fault data. It provides tools for fetching error lists and retrieving detailed fault information from Honeybadger projects.