"Information about sandbox environments or games" matching MCP servers:

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.

Get information about the current operating environment

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 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.

Query and interact with kubernetes environments monitored by Metoro. Look at APM, metrics, traces, profiling information with LLMs.

Enables AI assistants to monitor and analyze Proxmox VE virtualization environments via the MCP protocol.

An MCP server for the Liongard platform, providing tools to manage inspectors, systems, metrics, alerts, and environments through Liongard's API.

Enables complete management of CheckMK monitoring environments through natural language, including live monitoring, downtime scheduling, problem management, and configuration.

Provides Claude with access to Shodan for IP address lookups, service discovery, and vulnerability scanning, allowing users to query information about hosts, count results, and check API usage.

Provides read-only access to query and retrieve information about devices, fleets, events, and configurations managed by Flight Control through a safe integration layer supporting filtering and selector-based queries.

An open source MCP server empowering SREs with intelligent observability, predictive analytics, and AI-driven automation across Kubernetes, OpenShift, and Tekton environments.

Enables integration with Datadog APIs to monitor and retrieve information about monitors, metrics, dashboards, logs, events, and incidents through the Model Context Protocol.

Enables AI assistants to query and fetch error and performance monitoring data from AppSignal through the Model Context Protocol. Supports searching and retrieving detailed information about application errors and performance samples with flexible filtering options.

A read-only MCP server that exposes Hatchet client / REST observability APIs to coding agents across multiple environments from one process.

Enables comprehensive system monitoring and diagnostics through 18 tools that provide detailed information about CPU, memory, disk usage, network interfaces, running processes, battery status, hardware details, and temperature monitoring. Allows users to query system information and performance metrics through natural language interactions.

Enables management of oVirt / Red Hat Virtualization environments via AI assistants, supporting VM lifecycle, power operations, snapshots, and infrastructure queries.

An MCP server that connects to Sentry.io or self-hosted Sentry instances to retrieve and analyze error reports, stack traces, and debugging information.

Read-only MCP server for querying Jaeger environments from Codex, returning compact, sanitized trace summaries to protect sensitive data.

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.

Enables agents to interact with the Logflare API by writing JavaScript functions that run in a Vercel Sandbox, using three tools: search, execute_read, and execute_write.