"Methods to Improve Development Productivity Using MPC (Model Predictive Control)" matching MCP servers:

Enables LLM agents to monitor Mac thermals and control fan speed with safety limits enforced by a root daemon.

Enables AI agents and MCP clients to audit, monitor, diagnose, and safely manage Grandstream UCM phone systems, including extension status, call reports, site reconciliation, and confirmed test calls or admin edits.

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

Real-time cluster health monitoring, pre-request NLMS latency prediction, and intelligent prompt routing across multi-instance LLM backends (vLLM, Ollama, SGLang, TGI).

MCP servers for real-time development monitoring and interactive pair programming.

Enables automated review and analysis of network security controls (AWS Security Groups, Network ACLs) using natural language queries. Supports NSC configuration reviews, network segmentation testing, and identifying security gaps through conversational LLM interaction.

Enterprise AI governance layer for spend tracking, runtime guardrails, policy enforcement, and budget limits. Connects Claude, ChatGPT, and any MCP client to ThinkNEO's control plane for SOC2/GDPR/HIPAA compliance monitoring and real-time provider health.

Provides read-only access to query and retrieve information about devices, fleets, events, and configurations managed by Flight Control through a safe integration layer supporting filtering and selector-based queries.

Provides Claude access to RescueTime productivity data, enabling users to query daily summaries, top activities, category breakdowns, and productivity trends through natural language.

Provides access to RescueTime productivity data including daily summaries, activity tracking, productivity trends, category breakdowns, and hourly analysis to help understand and optimize time usage patterns.

Real-time supply chain risk intelligence with 25 tools: Global Disruption Index, Manufacturing Index, commodity prices, port congestion, border delays, chokepoints, air cargo, trade policy, energy, rail, freight, economic indicators, predictive signals, and AI intelligence briefs.

Enables brand visibility monitoring across major AI platforms like ChatGPT, Claude, Gemini, and Perplexity. It allows users to track visibility scores, analyze competitor data, and receive actionable insights to improve AI-generated brand recommendations.

Connects LLMs to Google PageSpeed Insights to analyze web performance, accessibility, SEO, and best practices, enabling AI assistants to audit and improve any web page.

Enables tracking and analyzing development time through the Wakapi API. Provides tools to retrieve coding statistics, project details, leaderboards, and recent activity logs for productivity insights.

Enables AI assistants to manage factory operations through MCP, providing tools for real-time telemetry, predictive maintenance, inventory forecasting, order estimation, and AI supervisor copilot capabilities.

Provides KPI tools for factory intelligence, including productivity, quality, downtime metrics, and alarm analysis via TimescaleDB.

An interface that allows large language models like Claude to interact with ActivityWatch time tracking data through the Model Context Protocol, enabling queries about application usage, browsing history, and productivity patterns.

Enables monitoring and control of the SST development process by streaming dev logs, managing Lambda invocations, and executing lifecycle commands like start, stop, and restart. It provides real-time access to event streams and deployment status directly through the Model Context Protocol.

Enables read-only interaction with OctoWatch DLP Cloud, allowing users to query risks, anomalies, user activity, productivity, and reports via natural language.

MCP Server for notify to telegram / weixin