MetricFire MCP Server
Monitor your infrastructure using natural language and AI
What it does
Connect the MetricFire Model Context Protocol (MCP) Server to AI assistants like GitHub Copilot and use simple prompts to search metrics, visualize data, create alerts, and manage your monitoring environment, without writing API calls.
A suite of hosted open-source tools that help developers monitor and fix issues with their technology. Get a free 14-day trial!HG-CLI | MetricFire
MetricFire's HG-CLI tool simplifies the installation, configuration, and management of monitoring agents, eliminating the need for complex manual configurations. With support for both a Command Line Interface (CLI) and a Terminal User Interface (TUI), you can quickly set up and manage your monitoring agents with minimal effort. Install the tool on any OS: curl -s "https://www.hostedgraphite.com/scripts/hg-cli/installer/" | sudo sh Instantly start collecting metrics and visualizing them in your MetricFire dashboard. Automatically configures Telegraf and other monitoring agents, removing the need to manually edit intimidating config files. Install, update, and manage agents within minutes,…from metricfire.com
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MCP-Builder.ai11d ago · mcp-builder.ai · ▲174The fastest way to connect your data with your AI Tools.
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Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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