AdsAgent
osted MCP for Meta, Google & TikTok in Chatgpt/Claude/Cursor
What it does
AdsAgent is a hosted MCP (Model Context Protocol) for Meta, Google Ads, and TikTok — not a fully autonomous media buyer. Connect Chatgpt, Claude, Cursor, or other MCP clients, then run insights, copy/recreate, and safe ops with operator approval on consequential changes. Install via Claude/Cursor plugins or the AdsAgent dashboard. Public skill pack on GitHub. Start at adsagent.md/connect
Install the AdsAgent skill pack, add hosted MCP in ChatGPT, Claude, Cursor, Codex, Gemini, and Grok, and find official GitHub, MCP Market, and LinkedIn links to start tri-channel ad ops.
adsagent.md is the canonical product site. Connect hosted MCP first in ChatGPT, then Claude, then Cursor, Codex, Gemini, and Grok. Use this page for setup, the public AI skill pack, GitHub, MCP Market, adsagents LLC on LinkedIn, and founder August Leung. AdsAgent is a hosted MCP. Start in ChatGPT Apps or a ChatGPT custom connector, then use the same OAuth endpoint in Claude. Cursor, Codex, Gemini, and Grok follow the same operator contract. In ChatGPT, add AdsAgent as an app or custom connector. Use https://adsagent.md/mcp/v2. Complete AdsAgent login in the browser — ChatGPT custom connectors deep-link into /oauth/authorize. Then connect Meta, Google Ads, or TikTok accounts you own. In…from adsagent.md
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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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