"Understanding High-Level Control Systems" matching MCP servers:

Enterprise AI operator evaluation MCP server. 27 tools (22 read + 5 write) for measuring, benchmarking, diagnosing, and interv ening on how human operators use AI tools across 5 canonical metrics.

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.

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

Enforces identity-based access control and audit logging for MCP servers, letting you grant fine-grained tool permissions to users and systems while failing secure by default.

A high-performance control plane for Ollama-based local LLM sessions with background memory consolidation, hybrid cloud planning, and real-time fleet monitoring.

A lightweight MCP server that enables AI assistants to deploy, inspect, and operate Kubernetes workloads through high-level workflow tools, reducing token usage with structured outputs.

Maple is a unified MCP server for agent observability, safety control, and behavior evolution, acting as a monitoring and auditing layer for high-agency agents. It enables developers to capture session timelines, replay risky branches, detect anomalies using ML, and enforce action guardrails.

Provides a scalable, containerized infrastructure for deploying and managing Model Context Protocol servers with monitoring, high availability, and secure configurations.

A unified MCP server providing observability, safety control, and behavior evolution for high-agency AI agents through tracing, replaying, and auditing. It features real-time firewall guardrails and ML-driven anomaly detection to monitor, block, or fork agent actions based on risk.

MCP server exposing rlg (RustLogs) log files as tools for on-call / SRE agent workflows. Three tools over JSON-RPC stdio — tail_log (last N events, filtered by level/target), filter_log (predicate filtering), summarize_errors (grouped error taxonomy). Pure Rust. MIT OR Apache-2.0.

MCP server for Blue Iris NVR, enabling camera health checks, live/historical snapshots, clip/alert search, and PTZ control via the Blue Iris JSON API.

A drop-in Model Context Protocol (MCP) server that lets an AI agent query PostgreSQL — read-only, enforced at the database level, with real SQL validation, timeouts, cost limits, OAuth 2.1, and an audit trail.

A read-only MCP server that enables LLMs to inspect and analyze ROS 2 systems through natural language, covering nodes, topics, parameters, actions, rates, QoS, and environment health. It can run without ROS 2 installed and safely surfaces runtime system state for diagnosis.

Lets AI agents query, manage, and operate their LLM observability data directly from the conversation. Provides 87 tools for cost analysis, alerting, anomaly detection, and runtime control gates.

agent-bom v0.105.0 is an open security scanner and self-hosted control plane for AI, MCP, and cloud infrastructure. The default scan profile in MCP server mode exposes 8 MCP tools. Additional profiles provide inventory, findings, compliance, graph, and runtime workflows.

Offline MCP server with runbooks for high-volume logs, metrics, traces, and event streams. Search and diagnose symptoms without external dependencies.

Enables AI assistants to search logs, query metrics, manage dashboards, analyze APM traces, and control monitors via Datadog APIs.

An evidence-first Prometheus MCP server that lets AI agents query production telemetry with detailed receipts including exact PromQL, timing, series count, and explicit warnings for empty, high-cardinality, or unreliable data.

Runtime access for AI coding agents to observe and control Android and iOS apps.

Enables MCP clients and AI agents to inspect a running FLECS application through its built-in REST API, including querying entities, reading components, explaining queries, and inspecting systems and performance statistics. With explicit opt-in, it also allows small reversible changes to the live ECS world.