AgentTakt

io.github.ryoohshima由 GitHub 帳號 ryoohshima 發布v0.2.2更新於 Oct 24, 2026

Review, edit, and approve AI agent task plans in a ComfyUI-style visual node editor in your terminal

已驗證STDIO僅桌面效率與工作流開發者工具

概覽

AI 產生的概覽

AgentTakt 讓 AI 代理提交任務計畫,你在終端機介面中以節點圖形式審閱、編輯並核准後,計畫才會被執行。

可以做什麼
接收代理提交的計畫,並在另一個終端機視窗中呈現為節點圖,包含節點、相依邊和依類型著色。用滑鼠和鍵盤編輯圖:移動、新增、刪除節點,繪製相依邊,修改參數。核准或拒絕計畫,並將編輯後的計畫 JSON 回傳給代理執行。僅顯示計畫而不阻塞代理等待核准。驗證圖結構(包括環路偵測),並把錯誤回傳給代理自行修正。
適用情境
當你希望在 AI 編碼代理執行多步驟計畫前設置人工確認環節,或希望以視覺化圖形而非文字方式檢視和調整代理計畫時使用。
執行需求
以 Python 套件形式透過 stdio 在本機執行(需 Python 3.10+,通常用 uvx 啟動)。需要兩個行程:由代理用戶端啟動的 MCP 伺服器,以及你在獨立終端機中啟動的 TUI。需要支援滑鼠回報的終端機模擬器。用戶端中 request_approval 的工具逾時需設得夠長,例如 30 分鐘。
安裝前請注意
核准工具會一直阻塞到你做出決定,用戶端逾時過短會中斷請求。TUI 必須已在執行,否則核准呼叫會失敗。TUI 啟動時會在背景檢查 PyPI 更新,除非設定 AGENTTAKT_NO_UPDATE_CHECK。核准後的計畫會回傳給代理執行,請仔細審閱修改。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 AgentTakt,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

[AgentTakt — Review, edit, and approve AI agent task plans in a ComfyUI-style visual node editor, right in your terminal.]

[PyPI - Version] [PyPI - Python Version] [License: MIT]

[AgentTakt demo: drag nodes, draw a dependency edge, approve]

AgentTakt is an MCP (Model Context Protocol) server and TUI tool. When an AI agent (an "Executor" such as Claude Code) sends a task execution plan over MCP, AgentTakt renders it as a node graph in your terminal. You review it with mouse and keyboard — move, add, and delete nodes, draw dependency edges, edit parameters — then approve, and the edited plan JSON is returned to the Executor for execution.

Claude Code (Executor)   │ stdio (MCP)                        your other terminal   ▼                                           │[agenttakt serve] ── Unix domain socket ──▶ [agenttakt (TUI)] MCP server                               review / edit / approve

Features

  • Terminal-native — no web UI; everything runs inside your terminal
  • Visual node editor — rounded nodes, dependency edges, and per-type coloring, powered by Textual
  • Mouse-first editing — drag nodes to move them, draw edges between ports (rubber band), click to select and delete
  • Safe approval loop — cycle detection (DAG guarantee) and other validations at the entry point, returning errors the agent can self-correct

Requirements

  • Python 3.10+ (recommended: uv)
  • A terminal emulator with mouse reporting (iTerm2, WezTerm, kitty, Ghostty, ...)

Installation

If you have uv, no installation is needed. uvx agenttakt fetches and runs AgentTakt on demand, and the .mcp.json example below starts the MCP server the same way.

If you don't have uv, install AgentTakt once:

sh
brew install ryoohshima/tap/agenttakt    # Homebrewpipx install agenttakt                   # pipx

Installing is also handy for everyday use even with uv — you start the TUI by hand, so plain agenttakt beats typing uvx agenttakt each time:

sh
uv tool install agenttakt

Agent Plugins

This repository is an Agent Plugins 1.0.0 package. In a compatible client, load the repository root as the plugin directory:

text
AgentTakt/├── plugin.json     # Portable plugin manifest├── mcp.json        # MCP server configuration└── LICENSE

The plugin requires uvx on PATH and runs the published agenttakt package from PyPI. Its uv cache is stored under the client-managed PLUGIN_DATA directory. Start the TUI separately with uvx agenttakt before using the tools. For request_approval, configure a sufficiently long tool timeout in your client (for example, 30 minutes); the portable MCP format has no timeout field.

The development .mcp.json is a separate client-native configuration that runs the local checkout. server.json supplies metadata for the MCP Registry.

Quick Start

AgentTakt runs as two processes: the MCP server, which Claude Code starts for you, and the TUI, which you start yourself in a separate terminal. The TUI is what displays the plan, so start it before asking the Executor for approval.

┌─ Terminal A: you ───────────────────┐   ┌─ Terminal B: Claude Code ───────────┐│ $ uvx agenttakt                     │   │ $ claude                            ││                                     │   │                                     ││   ╭─ grep ───╮                      │   │ > Plan the refactor, then ask       ││   │ pattern  │───╮                  │   │   me to approve it                  ││   ╰──────────╯   │                  │   │                                     ││             ╭────▼─────╮            │   │   calls request_approval(plan)      ││             │   edit   │            │   │   waiting for approval...           ││             ╰──────────╯            │   │   (blocked until you decide)        ││                                     │   │                                     ││   [a] Approve   [r] Reject          │   │                                     │└─────────────────────────────────────┘   └─────────────────────────────────────┘             ▲                                                    │             ╰──────────────── Unix domain socket ────────────────╯

Running the TUI in the same session as Claude Code does not work. A stdio MCP server has its standard input and output reserved for protocol traffic, so the same process cannot also drive a full-screen terminal UI. That is why the two halves are separate processes talking over a Unix domain socket.

1. Start the TUI (in its own terminal)

sh
uvx agenttakt           # if installed: agenttakt (short alias: agt)

An idle screen appears, waiting for plans from the Executor. Leave this terminal open. If no TUI is running when the Executor calls request_approval, the call fails with:

AgentTakt editor is not running. Ask the user to run "agenttakt" in a separate terminal, then call request_approval again.

On startup the TUI checks PyPI in the background and shows a notification when a newer version is available. Set AGENTTAKT_NO_UPDATE_CHECK=1 to disable the check.

2. Register the MCP server with the Executor (Claude Code)

Add the following to your project's .mcp.json:

json
{  "mcpServers": {    "agenttakt": {      "command": "uvx",      "args": ["agenttakt", "serve"],      "timeout": 1800000    }  }}

[!IMPORTANT] Setting timeout (milliseconds) explicitly is required. The request_approval tool blocks until the human finishes reviewing. MCP progress notifications do not extend client-side timeouts, so the default would cut the request off before approval. The example above sets 30 minutes (1800000). This does not apply to show_plan, which returns as soon as the TUI receives the plan.

3. Request approval from the Executor

When the Executor calls the MCP tool request_approval(plan, summary), the plan appears in the TUI as a node graph. Once the human edits and approves (or rejects) it, the result is returned as:

json
{ "status": "approved", "plan": { "...edited plan..." }, "reason": null }

See docs/schema.md for the plan JSON format and what to write in each node.

Display-only plans (show_plan)

show_plan(plan, summary) shows a plan in the TUI without waiting for approval — it returns {"status": "displayed"} as soon as the editor receives it. Use it when you just want visibility into what the agent is planning, in any mode (not only plan mode). The plan opens with a [view-only] header; closing it sends nothing back to the Executor.

Agents call request_approval naturally when the host is in plan mode, but they will not volunteer plans outside it. To encourage that, add an instruction like this to your project's CLAUDE.md (or equivalent agent instructions):

markdown
## AgentTakt
Whenever you formulate a multi-step plan — in any mode, not just plan mode —submit it with the AgentTakt `show_plan` tool so the human can see it as anode graph. Use `request_approval` instead when you need the human's approvalbefore executing.

Note: a [view-only] plan occupies the editor until dismissed; a later request_approval waits in the queue behind it.

Debug mode (try it without MCP)

sh
uvx agenttakt open examples/sample_plan.json --out edited.json

Loads a plan from a file, opens the editor, and writes the approval result to --out.

Key Bindings

KeyAction
aApprove the plan (confirmation dialog)
rReject the plan (with a reason)
nAdd a node
d / DeleteDelete the selected node/edge
u / UUndo / Redo
Arrow keysMove the selected node by one cell (fine-tuning)
EscapeClear selection
pToggle the parameter panel
?Help (controls and how to write type / data)
qQuit

Mouse: drag a node to move it; drag from a node's output port (●, right edge) and release on another node to create an edge.

Edges are drawn as braille Bezier-like curves by default. If they render poorly in your environment, switch to rounded orthogonal lines with --edges orthogonal.

Documentation

  • Plan JSON schema — data model, node fields, what to write in type / data, and validation rules
  • Changelog — release notes for each version

License

MIT

來源:README.md,提交 a36a2bd

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

2
  1. v0.2.2最新Sep 23, 2026
  2. v0.2.1Sep 16, 2026

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