"Information on memory banks or task managers" 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.

Enables capturing a tamper-evident, hash-chained local record of every AI agent tool call — both the decision before a tool runs and its outcome — so you can review what the agent actually did in order, detect edits, deletions, or reordering at the exact index, and export a signed evidence pack any third party can verify with no installs.

MCP server that diagnoses ML model regressions by correlating drift reports, eval runs, and deploy logs, providing evidence-cited incident reports through a set of investigation tools.

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

A Linux system monitoring MCP server that provides real-time information on CPU, memory, disk, network, processes, Docker, security, and more via MCP tools.

Identifies resource-intensive processes on macOS across CPU, memory, and network usage, with tools for detailed process filtering and system overview.

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

A task manager's view of a Windows or Linux PC for AI assistants: processes, per-core CPU and who ran on it, disks and the files they serve, network connections and DNS lookups, GPUs, sensors, services, stutters and a 7-day history. Actions (ending or suspending processes, controlling services, memory dumps) are allowed kind by kind, and it runs locally over stdio or on 127.0.0.1 only.

A lightweight server that provides real-time system information including CPU, memory, disk, and GPU statistics for monitoring and diagnostic purposes.

Provides persistent shared memory and multi-agent coordination for MCP-compatible coding agents on Zerops, with a live Observatory dashboard for monitoring activity.

Enables read-only observability of Windows systems, exposing CPU, memory, storage, service, and health information through Model Context Protocol tools.

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

This server enables coding agents to share local memory and receive scoped task context. It provides live visibility into agent operations and allows the application of structured project skills.

An observable autonomy harness for AI coding agents that enables long task execution without drift or cheating, while recording all actions for cost and quality steering.

Provides read-only access to Tactical RMM, enabling agent searches, detailed agent information, audit log queries, and execution of information-gathering PowerShell scripts on agents, with Entra ID authentication and a strict read-only guard.

Provides five read-only tools for AI agents to inspect host system information, memory, disk usage, log tails, and overall health. Enforces path allowlisting and rejects credential-like files to keep local inspection safe and constrained.

Enables an agent to launch or attach to a running application and profile startup phases, CPU, memory, memory bandwidth, GPU and network activity on one live timeline, capturing call stacks and hot functions. It then ties the measured hotspots to the user's own code and reports which interactions cost time or retain memory.

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.

Enables MCP-compatible clients to inspect the local machine's CPU, memory, and disk information through tools, a structured resource, and an upgrade-assessment prompt.

An MCP server that connects to Sentry.io or self-hosted Sentry instances to retrieve and analyze error reports, stack traces, and debugging information.

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.

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

8 standalone MCP servers for SMBs — Guardrails (prompt injection, PII, secrets detection), FinOps (AI cost tracking and budgets), Observability (agent tracing), Smart Router (17+ models, 9 providers), Trust Score (governance scoring 0-100), Memory (persistent agent memory), ThinkSecure (runtime security + SOC2/GDPR audit), and A2A Lite (agent-to-agent protocol). 37 tools total, TNC credits

16-tool MCP server for Google PageSpeed Insights & Chrome UX Report APIs. Analyze, compare, and optimize web performance directly through Claude, Cursor, or any MCP-compatible AI client.

Read-only MCP server for Grafana Loki: lets AI agents (Claude Code, Cursor, Copilot) discover labels, read bounded LogQL pages, count lines by label or time, and export logs — across several Loki stands

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.

Tells an agent what went wrong with its own Ollama calls, in sentences with the fix: lost prompt cache and where the prompt stopped matching, context overflow, a model running partly on CPU, tool schemas crowding the prompt. Also the last turn in numbers and which local models fit in video memory. Local, read-only, nothing leaves the machine.

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.

Uptime monitoring for websites, APIs, SSL certificates, domain expiry, ping and TCP/UDP ports. 15 tools to list, create, pause and delete monitors, pull incident timelines with error codes, and read hourly or daily uptime and response-time statistics.

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.

MCP server for the Chrome UX Report, providing real-user Core Web Vitals (LCP, INP, CLS) and historical trends for any origin or URL via natural language queries.

Enables AI assistants to search, summarize, and inspect Kibana/OpenSearch Dashboards logs through the user's logged-in browser session, eliminating the need for API keys or service accounts.

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 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.

An MCP server that exposes a dbt project's run state as tools, enabling AI assistants to answer questions like 'is the warehouse healthy?' or 'what broke and why?' via plain English, using read-only access to dbt artifacts and warehouse data.

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.

A lightweight npm MCP server for deep Redis diagnostics, offering tools for memory, slowlog, clients, keyspace, latency, and config analysis with AI-powered recommendations.

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.

Laravel Telescope-style debugging for Hono apps whose dashboard endpoint is also an MCP server: read recent exceptions with the request that produced them, recent requests filtered by status or duration, one request in full, and the slowest queries. Five read-only tools, zero runtime dependencies.