"Recently updated information from 2 hours ago" 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.

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.

A Model Context Protocol server that connects to AppSignal, allowing users to fetch, list, and analyze incident information from their AppSignal monitoring.

A read-only MCP server for bounded semantic inspection of ROS 2 perception systems, enabling discovery and metadata extraction from sensors such as cameras, depth sensors, and LiDARs without device configuration or actuation.

Enables AI assistants to retrieve and analyze Sentry issues, including error reports, stacktraces, and debugging information from Sentry.io.

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

An MCP server that enables querying logs and metrics from Graylog, Prometheus, and InfluxDB 2.x. It provides tools for executing Lucene log searches, PromQL queries, and Flux queries directly within MCP-compatible clients.

This server provides tools to inspect error reports, stacktraces, and other debugging information from your Sentry account.

Enables querying logs and metrics with plain SQL from any MCP client via pooml's read-only query API.

Enables classification of GPU workloads as training, inference, or idle from telemetry data, with tools for one-shot classification, benchmarking, and audit log verification.

Provides MCP tools to create and query SigNoz trace funnels, enabling agents to measure their own step conversion rates from within the agent loop.

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.

Unofficial MCP server for Vexo analytics. Enables querying event names, counts, timelines, sessions, and recent events from Vexo Export API through natural language.

Compares AI coding tool spend before and after a migration -- Cursor, Claude Code, GitHub Copilot, OpenCode, Codex CLI -- via an MCP server, real numbers from each vendor's own API or local logs.

Provides a local MCP interface to query captured, PII-scrubbed prompt telemetry from coding agents and browser chats, enabling time summaries, prompt search, and activity analysis without data leaving the machine.

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.

Enables coding agents to read performance findings from sixty, get detailed evidence for each finding, and close or resolve them with descriptions, while also checking service telemetry and providing installation instructions.

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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.