"Understanding Unrestricted Model Abilities" matching MCP servers:

Enables AI agents to monitor server health and capacity, diagnose outages, inspect Docker and deployment status, and perform safe, bounded recovery actions via MCP without granting unrestricted shell or SSH access.

Enables secure, read-only inspection of a VPS over SSH through approved operations such as system health, disk usage, container logs, and service status, without giving the AI unrestricted shell access.

A secure, local-first MCP server for read-only inspection and troubleshooting of development environments, exposing narrow, typed, auditable capabilities for repository inspection, log summarization, Docker review, and security scanning without granting unrestricted machine access.

Provides cryptographically signed, tamper-evident compute usage receipts via a Model Context Protocol server, exposing tools to record usage, verify receipts, list the ledger, and verify ledger integrity without requiring any account, API key, or single cloud provider.

Model Context Protocol (MCP) server for debugging, analyzing, and diagnosing Kubernetes clusters directly from AI agents.

Relays error logs from other MCP servers when an LLM call fails and the returned error message is unclear, helping the model handle errors more intelligently.

Enables an LLM agent to investigate a Kong Gateway through fourteen read-only, schema-validated tools and a deterministic diagnostic engine, so it can trace routes, services, plugins and upstream health and explain faults such as why authentication is failing on a path. Every fact comes from the gateway itself, and the model only selects tools and writes the evidence-backed explanation.

Model Context Protocol server for Verlon AI that exposes gates, logs, recommendations, and experiments as MCP tools, enabling coding agents to inspect and manage AI infrastructure natively.

An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.

Real-time cost observability for Model Context Protocol tool calls. Wraps any MCP server, attributesspend per tool/project/customer. Free 25K calls/month. EU-hosted, GDPR-ready, MIT.

Radar is an open-source Kubernetes observability and diagnostics MCP server. It exposes cluster health, workload diagnosis, logs, events, topology, audit findings, and remediation actions to AI agents through the Model Context Protocol.

A Model Context Protocol (MCP) server that lets an AI assistant read and operate the Lumics network monitoring platform via its REST API.

A locally-hosted MCP (Model Context Protocol) server that gives Claude real tools to debug Docker containers — fetch logs, inspect memory/CPU, and run diagnostic commands inside a container, all from a chat with Claude Desktop.

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.

Prediction stability engine for AI agents. Evaluate model stability, detect ghosts, probe any LLM for instability, monitor fleet drift. 20 tools + 1 resource. Works with Claude, Cursor, VS Code.

Exposes network-monitoring tools (query metrics, analyze windows, compare, logs, status, runbooks, speed tests) as an MCP server for agentic workflows. Designed with evaluation suites, cost-aware model routing, and semantic tool retrieval.

Enables building, validating, describing, and conformance-testing TTEOP telemetry envelopes through the Model Context Protocol.

A Model Context Protocol server for Zoho Site24x7 that uses a JavaScript sandbox to execute API calls, enabling management of monitors, accounts, and MSP/BU tenancy through natural language.

An MCP server that exposes GPU-accelerated anomaly detection to AI assistants via the Model Context Protocol. Provides two MCP tools: waveguard_scan (send training + test data in one call, returns per-sample anomaly scores and top explanatory features) and waveguard_health (check API and GPU status). Works on time series, JSON, numbers, text, and images — fully stateless.

Enables AI assistants to monitor and manage Linux infrastructure including services, logs, processes, disk, memory, ports, cron, nginx, Docker, and system health checks via the Model Context Protocol.