"Integrating Claude Desktop with a Local LLM using the LMStudio API" matching MCP servers:

Windows desktop-control MCP server: screenshot, window mgmt, mouse/keyboard input, recording.

Enables benchmarking of Large Language Model APIs by measuring performance metrics such as generation throughput, prompt throughput, and Time To First Token (TTFT) with configurable concurrency levels and parameters.

MCP server for Windows desktop automation. It provides mouse, keyboard, screen capture, and AI-driven UI element detection via OmniParser.

Reports your Claude subscription usage (5-hour and weekly limits) with a forecast and velocity recommendation, using Claude Code's existing OAuth session without requiring an API key.

A Model Context Protocol server that provides AI assistants access to AWS CloudWatch Logs, enabling browsing, searching, summarizing, and correlating logs across multiple AWS services.

Provides tools for Claude to query local Claude Code token usage and cost data, enabling spend analysis and insights through natural language.

Provides Claude plan usage data (session and weekly percentages) as an MCP tool by reading through a logged-in browser, enabling Claude to check its own remaining usage.

Enables agents to check remaining Anthropic and OpenAI rate-limit quotas with reset times, plus Hermes Agent token usage, so bots can throttle or stop before hitting limits.

Enables querying and analyzing Claude Desktop/Code conversation history across all users on a machine, including conversation search, token usage statistics, model/tool insights, and opening a web dashboard for detailed visualization.

A 100% local development monitoring tool that captures browser console logs, network requests, and backend server output for analysis by AI assistants via MCP. It enables LLMs to debug applications by providing structured, real-time access to full-stack log data and persistent local storage.

Measured latency and uptime for 45 hosted AI inference APIs: independent probes from 4 regions every 5 minutes, no gateway. Exposes get_ai_api_latency (TTFB p50/p95 and uptime rankings by region). Data CC BY 4.0.

Enables retrieving real Claude subscription usage statistics, including the 5-hour session window, weekly limit, and per-model limits, from the same endpoint Claude Code uses.

An MCP server that exposes Claude Code's real-time rate limit usage so that an orchestrator can check remaining capacity before launching subtasks.

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

A fail-closed MCP server for Msty Studio on macOS that provides read-only diagnostics and an optional bounded local-generation tool, without accessing chats, keys, or configuration.

Provides structured access to Claude Code agent log files, allowing agents to query assistant lines and tool calls without reading raw JSONL data.

Fetches and tracks Claude.ai usage data including session and weekly limits with automated daily logging and persistent session management. It allows users to monitor their usage history directly through Claude Code integrated tools.

Provides LLMs with network intelligence capabilities including PTR record lookups, ASN analysis, traceroute enrichment, and real-time network monitoring through The Aleph API.

Maintenance, recovery, and observability for Claude Code. CLI + MCP server + dashboard.

Manage and monitor Hadoop clusters via Apache Ambari API, enabling service operations, configuration changes, status checks, and request tracking through a unified MCP interface for simplified administration. * Guide: https://call518.medium.com/llm-based-ambari-control-via-mcp-8668a2b5ffb9