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Vyra reimagines how we interact with AI.
Every session today begins the same way — re-explaining context, constraints, and past decisions. Chat history isn’t memory. It’s recall without structure.
Vyra introduces a persistent memory layer for AI agents — where decisions, architectures, and constraints evolve into structured context that follows your work.
Built entirely in Figma Make, this prototype explores memory as infrastructure — transforming AI interaction from reset-based sessions into continuous collaboration.
🔗 Live Project: https://joinvyra.figma.site/
#FigmaMakeathon
The network for creativity
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Host details interaction I made for an ongoing project.
An open-source MCP (Model Context Protocol) server that lets AI assistants like Claude work with X directly, using 11 tools built on the X API v1 and v2.
Agents can post and search content, look up and update profiles, follow and unfollow accounts, list followers and following, and create and manage public or private lists.
It's set up with environment-based API keys and stdio transport, plus GitHub Actions for publishing and releases. It's part of my open-source MCP series, alongside servers for LinkedIn, Medium, and Kaggle.
You've built MCP servers for a few different platforms now. Have you found any tool names or descriptions that made a noticeable difference in how reliably the agent chose the right tool? I'd be interested to hear what you ended up changing.