"A system or tool for enabling computer vision capabilities in an MCP (Microcontroller Platform)" matching MCP servers:

Provides system hardware information (CPU, memory, storage, etc.) and system status (OS, network, resource usage) via MCP tools.

A read-only MCP server that enables AI agents to act as GCP platform engineers, allowing them to investigate incidents, take inventory, and find cost-optimization opportunities in Google Cloud projects without mutating any infrastructure.

Enables monitoring of Ubuntu system metrics, Docker containers, and public IP drift, with Feishu alerting and HTTP/MCP tools for querying status, viewing history, and restarting containers.

Enables Claude to monitor CPU, memory, disk, processes, network connections, Docker containers, and system logs for system diagnostics and troubleshooting.

Read-only MCP server that exposes Kubernetes platform state (tenants, pods, SLOs, ArgoCD applications, chaos schedules, and catalog services) to AI agents, enabling natural language queries about cluster health and configuration.

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.

Lets your coding agent talk to the RunWhen platform — workspace chat, issues, SLXs, run sessions, and the Tool Builder — over the Model Context Protocol. Enables workspace chat with AI assistant, task authoring via Tool Builder, and direct data access to workspaces, issues, SLXs, run sessions, and more.

Enables AI agents to debug and repair historical Solaris/SPARC systems by providing an out-of-band control plane with guest DTrace, QEMU monitor access, SPARC-aware GDB, host eBPF/perf tracing, and an immutable evidence ledger for cross-layer hypothesis testing.

Read-only MCP server for observing Linux hosts (systemd, ZFS, Docker, VMs, network, hardware, NixOS) as a graph of objects with provenance. Provides seven tools to list hosts, get status, collections, objects, evidence, lookup, and changes.

Provides a unified MCP server to interact with multiple middleware (Loki, MySQL, Redis, RocketMQ, Elasticsearch, MongoDB) through a desktop application for connection management and configuration export.

A framework for building MCP servers with built-in enterprise capabilities such as authentication, authorization, telemetry, audit logging, and data classification, allowing domain developers to focus on business logic while maintaining governance and compliance.

Enables AI clients to access real-time system information such as memory and swap usage from a Linux machine via MCP tools.

MCP server that coordinates autonomous infrastructure health monitoring agents, enabling natural-language telemetry queries and automated diagnosis, remediation, and verification.

Enables live tracing and observability of MCP tool calls, persisting execution traces to MongoDB and streaming them in real time to a dashboard.

Enables LLMs to interact with Kibana through composable toolboxes for building dashboards, managing data, and handling alerts, among other operations.

Enables MCP hosts like ChatGPT and Claude to query data platform metadata, explore schemas and tables, inspect SQL explain plans, and monitor DAG and ETL status through standardized tools.

An enterprise MCP server scaffold that provides secure, governed access to internal tools through RBAC, audit logging, rate limiting, and prompt-injection boundaries, with a FastAPI control plane and OpenTelemetry observability.

Provides a read-only summary of Ubuntu server status including system version, resource usage, apt updates, service health, security logs, and hardware information to AI clients via MCP tools.

Enables LLMs to monitor system health, manage processes, execute shell commands, and inspect environment variables and directories.

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.