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Share, update, and continue local artifacts across MCP-enabled LLM tools.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "artifacty" yet — see the docs or source repo.
Publish the current API design draft as an artifact and list existing artifacts. Then continue from that artifact to generate a Python backend implementation plan without copying the full content into chat.
Returns published and listed artifact details, then generates a follow-up implementation plan from the artifact.
Read the previously saved competitor analysis artifact, update its conclusions section, and create a new artifact for the next-round interview outline.
Outputs the original artifact read result, the updated version, and a newly created interview-outline artifact.
List all local artifacts sorted by most recent update time, and highlight the top five artifacts worth continuing, each with a one-line purpose note.
Provides a time-sorted artifact list and recommends the most relevant artifacts to continue working on.
Persist, list, and hand off agent outputs with session metadata and deduplication.
Create and live-refresh local interactive web pages for rapid prototyping and demos.
Build complex multi-component web artifacts with React, Tailwind, and shadcn/ui.
Enable AI agents to read, write, search, and share files by URL.
Build complex web artifacts with React, Tailwind, and shadcn/ui components.
Plan artifact delivery routes to improve transport coordination and delivery efficiency.