"Movies available on Netflix" matching MCP servers:

MCP server for On-Call Health burnout analysis. Connects AI assistants to your on-call data for workload insights.

Provides read-only on-demand ServiceNow reports for system logs (syslog) and developer work (update set changes), with automatic pagination and date filtering.

MCP server exposing Radarr's v3 REST API as tools, enabling LLMs to read and manage movies, downloads, history, indexers, and more.

Provides structured MCP tools for local runtime observability and debugging of React Native/Expo apps on Android, enabling evidence-first diagnostics such as screenshots, UI trees, per-request network capture, performance metrics, and CDP-based console/heap/profiling exports.

MCP server for system monitoring, enabling users to ask about CPU, memory, disk, network, and processes on their system.

Bridges Microsoft Clarity's analytics API with Claude, enabling custom date ranges and page-level filtering on top of Clarity's native limitations.

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.

Enables log analysis for Tenable Patch Management (SaaS and on-prem) by parsing, de-duplicating, and decoding server/client logs into structured verdicts, ranked issues, and known-issue fixes.

It enables solo builders to automatically log product changes to PostHog and later get statistically honest verdicts on whether those changes moved key metrics, without needing enough traffic for A/B tests.

Tamper-evident audit logging for AI decisions. Three tools (record_decision, verify_decision, list_decisions) write to a regulator-grade ledger built on AWS S3 Object Lock with 7-year retention. Designed for EU AI Act Article 12 and FCA SS1/23 evidence requirements. Try zero-config: npx audit-ledger-mcp boots in sandbox mode against a public hosted tenant.

Read-only MCP server exposing AGmind Systems Lab's measured local-LLM benchmark claims (TTFT, inter-token latency, task success, etc.) on AMD Strix Halo and DGX Spark hardware via search, claim lookup, and measured-combination listing tools.

Enables interaction with Jira Service Management Operations alerts and on-call schedules, including searching alerts, reading notes and activity logs, acknowledging, closing, annotating, adding responders, and querying current and next on-call rotations.

Exposes live industrial IoT telemetry to any MCP client, streaming simulated sensor data from a fleet of machines and detecting anomalies, with the ability to inject faults on demand.

Enables agents to query GPU availability across SSH hosts, find free GPUs, list hosts, and inspect fleet status using only nvidia-smi on the remote side.

Verifies AI outputs in real-time across 6 dimensions, with automatic retry and failover to ensure correct, complete, and reliable LLM responses before they reach the user's editor.

Read-only AMD GPU monitoring for Claude on Linux — VRAM, temperature, clocks, power, and running ML processes via rocm-smi.

Enables SEO audits and URL monitoring via the SEO Radar API from any MCP-compatible AI client.

Enables AI assistants to query self-hosted OxiLytics analytics for app downloads, crashes, reviews, and sync health, with a read-only design that keeps data on your own server.

The logs of everything on one machine — app, build, GPU, containers, serial board, OS — interleaved in the order they happened, and readable by an agent. Read-only: it can tail, search and wait, and it cannot write, delete or configure anything.

Exposes a Kubernetes cluster to MCP-compatible AI clients, enabling read-only and optional write operations on cluster resources like pods, deployments, and namespaces through natural language.