
TaskChampion MCP
io.github.GabiUp2由 GitHub 帳號 GabiUp2 發布v1.0.4更新於 Oct 24, 2026
MCP server for Taskwarrior 3.x, TaskChampion, and Timewarrior task management.
概覽
讓 AI 助理透過本機的 task 與 timew 命令列工具讀取、建立、修改與完成任務,並管理時間紀錄。
- 可以做什麼
- 它包裝 task 與 timew 命令列工具,並將其暴露為結構化的 MCP 工具,讓助理可以讀取、加註、建立、完成與刪除任務,並管理時間項目。它附帶任務結構預設(minimal、gtd、scrum、kanban 以及一個自訂範例),用來向模型描述你的任務結構。首次執行有引導流程,用於設定角色與結構,相關工具包括 get_runtime_capabilities、get_initialization_status、propose_initialization_options、use_preset_schema、save_initial_schema 與 reload_configuration。
- 適用情境
- 當你已經用 Taskwarrior 3.x 或 Timewarrior 管理任務與時間,並希望助理協助專案規劃、任務拆分與時間追蹤,同時不交出任務資料庫控制權時,適合使用。它面向本機上的終端工作流程。
- 執行需求
- 以 stdio 方式在本機執行的程序,從 PyPI 安裝 taskchampion-mcp,用 uvx 或 pip 執行。需要 Python 3.10+、PATH 中的 Taskwarrior 3.x,時間追蹤功能可選需要 Timewarrior。在操作類工具可用前,必須在 ~/.config/taskchampion-mcp/config.toml 中設定 role 以及 schema 或 schema_path。未宣告驗證、環境變數或標頭。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 TaskChampion MCP,將其新增到工作區。
- 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
TaskChampion MCP
A Model Context Protocol server for Taskwarrior 3.x, TaskChampion, and Timewarrior.
For the bearded Unix jockeys and keyboard cowboys who manage their life from the terminal — and now want their LLM to lend a hand. 🧔⌨️
[PyPI version] [GitHub release] [License] [Python] [MCP Registry] [Glama]
Latest release: v1.0.4 — pip install taskchampion-mcp / uvx taskchampion-mcp
What Is This?
TaskChampion MCP is a Model Context Protocol server that lets LLMs read, create, modify, and manage your Taskwarrior tasks and Timewarrior time entries. It wraps the task and timew CLI tools and exposes them as structured MCP tools that any compatible AI assistant can call.
Why? The author self-hosts TaskChampion on a home server and wanted a clean way for LLMs to cooperate on project planning, task decomposition, and time tracking — without giving up control of the task database.
Supported Platforms
Requirements:
- Python 3.10+
- Taskwarrior 3.x (TaskChampion sync)
- Timewarrior (optional, for time tracking features)
Quick Install
Then configure your IDE's MCP settings to use:
Per-target install guides: Claude Desktop | Windsurf | Cursor | Neovim
First Run
On a fresh install with no config.toml, the server boots in onboarding mode. All tools are visible in tools/list, but operational tools return structured schema_unset errors until onboarding completes (ADR 19). You finish onboarding by persisting two keys in ~/.config/taskchampion-mcp/config.toml:
role— what the LLM can do (CONTRIBUTOR / GENERATOR / MANAGER)schemaorschema_path— which task schema the server validates against
Three ways to get there:
- Let the LLM walk you through it. Connect your IDE to the MCP server with no config and ask: "Help me set up TaskChampion MCP." The LLM calls
get_runtime_capabilitiesfirst, seesmode: "onboarding", then usesget_initialization_status->propose_initialization_options->use_preset_schema(orsave_initial_schema). The server auto-reloads on success -- no restart needed. - Run the CLI wizard:
./dev.sh init(interactive) or./dev.sh init --preset gtd --role CONTRIBUTOR --non-interactive(scripted). - Edit
config.tomlby hand -- see quick_start.md. Two keys, then callreload_configurationfrom the LLM (or restart the IDE).
The three paths are interchangeable and produce identical state. Pick by who should be doing the typing -- see initialization_flows.md for the decision guide.
Permission Levels
Control what the LLM can do with your tasks via three cumulative roles:
Set the role in ~/.config/taskchampion-mcp/config.toml:
Task Schemas
Taskwarrior supports custom workflows via UDAs (User Defined Attributes). TaskChampion MCP ships with schema presets that teach the LLM your task structure:
On first run, the MCP will prompt you to select a schema or auto-generate one from your existing tasks.
Security
This tool gives an LLM indirect access to your task management CLI. Security is not optional:
- No shell execution — all CLI calls use subprocess argument lists, never
shell=True - Input sanitization — all LLM inputs validated against allowlists before passing to CLI
- Rate limiting — configurable per-minute/per-hour caps prevent runaway loops
- Audit logging — every operation logged with timestamp, tool, parameters, result, and
result_code - Code-tagged envelopes — every tool response includes a stable
codefield for machine-safe branching - Dry-run mode — every destructive operation supports
dry_runpreview without mutation - Confirmation mode — lifecycle operations use explicit confirmation tokens when confirmation is enabled
- Sensitive field redaction — configurable fields hidden from LLM responses
See ADR 9, ADR 13, and ADR 14 for the full security and observability design.
Taskwarrior Compatibility
We focus on the modern Taskwarrior 3.x + TaskChampion stack. Taskserver (taskd) is deprecated and will receive limited support in a future version. See ADR 8.
Documentation
Troubleshooting
Common first-run and config issues. Detailed walkthroughs live in docs/manuals/quick_start.md and docs/manuals/initialization_flows.md.
For deeper failure modes, every MCP tool returns a stable error_code field (ADR 14) and every call is audit-logged (ADR 13) at ~/.local/share/taskchampion-mcp/audit.log by default.
Contributing
See docs/CONTRIBUTING.md for the full guide. Key points:
- Branch from
dev, PR toqa, release fromqatomain - Semantic versioning (
vMAJOR.MINOR.PATCH) - LLM-assisted contributions must be attributed (see
docs/llm_context/AGENTS.md) - All unverified assumptions must be logged in
docs/llm_context/assumptions_and_ideas.md
License
Apache License 2.0 — use freely for private and commercial purposes. Attribution required via the NOTICE file.
Copyright 2026 gabiup2
This project was bootstrapped with assistance from Claude claude-sonnet-4-20250514 via Windsurf Cascade.
來源:README.md,提交 f5af773
工具
0版本歷史
1- v1.0.4最新Sep 16, 2026
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