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dtyq/magic
Magicrew. The first open-source all-in-one AI productivity platform (Generalist AI Agent + Workflow Engine + IM + Online collaborative office system)
Don’t install what you can’t explain. Each of these free tools reads dtyq/magic when you swap github.com in its link for another address.
An interactive diagram of how the parts fit together. Generated by AI.
A written guide to the codebase, with a chat you can ask questions. Generated by AI.
Opens the code in VS Code in your browser. Needs a GitHub sign-in. Same as pressing . on any GitHub repo.
The whole project as a single text file to paste into Claude or another assistant. Large repos may not fit in one chat.
Or build it on your computer
npx techandria digest dtyq/magicBuilt from the current code, which Techandria hasn’t reviewed. The file says so at the top. Add --only src for part of a large repo.
A remote MCP server your agent can connect to and read the docs and code live while it works.
Add it to Claude Code
claude mcp add --transport http magic-docs https://gitmcp.io/dtyq/magicThe linked sites are independent services, not part of Techandria. They read the default branch as it is now, not the reviewed commit, and AI-written explanations can be wrong. Repository text you paste into an assistant can contain instructions aimed at it, so treat it as data. None of this is a security review.
Not available through Techandria. A library has no Techandria install path. Running an arbitrary program is a different risk from adding a reviewed skill.
You can still get the code from the source and read it yourself:
git clone https://github.com/dtyq/magicDiscovery metadata only. Nothing has been scanned or approved, so this is a listing — not a recommendation to run the code.
The badge shows this project's current review state and updates on its own — including if the state changes. It links back to this page.
[](https://techandria.com/project/dtyq/magic)No README could be fetched from GitHub for this repository.

Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-hosted, so teams move from prototype to production without rebuilding the stack.

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