Who it is forA professional with a busy inbox and chats who needs requests turned into tracked tasks, with drafted replies that wait for their sign-off.
The problemRequests arrive in mail, chats and trackers, and tracking them by hand means opening each system in turn.
The outcomeIncoming requests appear as tasks on one rail, an agent prepares the work and a draft reply, and you decide whether it goes out.
What you need first
- Python 3.10 or newer, or the Windows Taskuary.exe download, or Docker
- An AI provider key or a local Ollama model
- At least one inbound channel such as mail, chat or tickets
- A coding CLI such as Claude Code, Codex or Gemini if you want agents to do the work
Steps
- Install with
pip install taskuaryand start it withtaskuary. - Open http://127.0.0.1:7787 and, in the setup wizards, connect an AI provider or local Ollama model.
- Add at least one inbound channel, then choose the coding CLI that should receive tasks.
- Open a task and choose Send to agent, then read the prepared reply on the task.
- Edit the reply if needed and choose Approve & send only when it is ready.
Prompt for your agent
Use the ldbumble/taskuary repo to set up a local instance with `pip install taskuary` and `taskuary`, then connect the inbound channel <channel-name>. Report the task created from one incoming request and the state of its prepared reply. Verify that the reply is still unsent until the owner chooses Approve & send.
Caveat. The setup wizards test each connection, but you still need working AI and channel credentials, and the README does not list every supported inbound channel.
Use this in your AI agent
Ask your agent
Using the Deduped MCP, get the setup steps for ldbumble/taskuary and "Turn work mail into tasks you approve before anything sends"
Add Deduped to Claude Code once
claude mcp add --transport http deduped https://dedupedai.com/mcp
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