
Toddyi
io.github.toddyi-appv0.2.7更新於 Oct 11, 2026
Tasks, calendar and study materials in Toddyi: search, read and plan with your tasks.
概覽
讓助理讀取和修改已登入帳號在 Toddyi 中的任務、資料夾、學習素材、卡片牌組和知識圖譜。
- 功能
- 把 Toddyi 的任務、資料夾和學習素材操作暴露為 MCP 工具,包括 list_tasks、get_task、create_task、update_task、complete_task、reopen_task、archive_task、delete_task、list_folders 和 create_folder。學習類工具可列出、搜尋、讀取、更新、加標籤和刪除學習資產、註解、牌組、知識圖譜節點與關聯、集合、分享連結、片段和發佈內容。遠端端點提供日常工具,本機 CLI 伺服器則提供包含學習編輯在內的完整工具集。
- 適用情境
- 適合任務、截止日期、資料夾和學習素材已經放在 Toddyi 中,並希望助理在對話裡規劃、搜尋、彙整或更新它們的情境,例如詢問哪些已逾期,或把筆記整理成任務。
- 執行需求
- 可以使用 toddyi.love/mcp 的遠端端點並透過 OAuth 登入,也可以在本機執行 toddyi 二進位檔並以 toddyi mcp 透過 stdio 提供。本機方式需要 Toddyi 帳號,以及 toddyi login 產生的權杖,或設定 TODDYI_TOKEN 環境變數(連接其他伺服器時還需 TODDYI_URL)。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Toddyi,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。
其他 MCP 客戶端
把它新增到你客戶端的 mcpServers 設定中。
{
"mcpServers": {
"toddyi": {
"type": "http",
"url": "https://toddyi.love/mcp"
}
}
}README
toddyi — Toddyi from the terminal
A single binary for people, shell scripts, CI jobs and AI agents: read and change your Toddyi tasks without opening the app.
Install
Download the binary for your platform from
Releases — one static
file, no dependencies — check it against SHA256SUMS, and put it on your PATH.
Or with Go 1.24+:
Building from source:
Signing in
toddyi login shows a code and opens the approval page in your browser. You
approve it there, signed in as you normally are — second factor included — and
the CLI collects a token of its own. The CLI never sees your password.
- The token is stored in
~/.config/toddyi/config.json(mode 0600). toddyi logoutrevokes it on the server, not just locally.- Every signed-in terminal is listed at /cli/tokens, where any of them can be revoked.
- For CI or an agent that should not write files, set
TODDYI_TOKEN(andTODDYI_URLfor a server other than toddyi.love) instead of logging in.
Commands
Both word orders work: toddyi create task … and toddyi task create ….
Flags may come before or after the arguments. toddyi <command> -h lists a
command's flags.
An asset keeps the same ID across all versions. A workspace stores those IDs,
version numbers, file paths and SHA-256 checksums in .toddyi-assets.json.
sync keeps a local edit if the remote version also changed and reports a
conflict instead of overwriting either copy. New files in the workspace are
uploaded as private assets; deleting a tracked file creates a recoverable
remote deletion, and asset restore ID VERSION can bring it back.
Dates are read in your account's time zone: today, tomorrow, yesterday,
+3d, +2w, 2026-10-01, 2026-10-01T09:30, or none. A day without a time
is the end of that day for a deadline, so "due today" is not overdue at
breakfast.
For scripts and automation
--jsonon any command prints JSON on stdout; errors go to stderr as{"error": {"code", "message", "status", "exit_code"}}.- Exit codes are stable:
0ok,1error,2usage or a value the server could not read,3not logged in / token revoked,4not found,5the Free plan's task limit. - stdin:
toddyi create task -makes one task per line;done,reopen,archive,showanddeleteread ids from stdin when none are given.
For AI agents: toddyi mcp
toddyi mcp is a Model Context Protocol
server on stdio. It exposes the same operations as tools — list_tasks,
get_task, create_task, update_task, complete_task, reopen_task,
archive_task, delete_task, list_folders, create_folder, whoami —
and Study tools: list_study_assets, search_study_assets (query plus optional kind, visibility, tag, and created/updated date bounds),
get_study_asset, update_study_asset, delete_study_asset, tag_study_asset,
restore_study_asset_version,
reprocess_study_asset_extraction,
analyze_study_asset,
list_study_annotations, create_study_annotation,
update_study_annotation, delete_study_annotation, and analyze_study_crop.
Flashcard tools are list_study_decks, get_study_deck, push_study_deck,
clone_study_deck, import_public_study_deck,
restore_study_deck_version, and set_study_deck_public.
list_study_knowledge_graph, create_study_knowledge_node,
update_study_knowledge_node, delete_study_knowledge_node,
link_study_knowledge_nodes, and delete_study_knowledge_relation. They use
the logged-in account's token and the same owner-scoped server rules. Knowledge nodes can be marked as primary
source facts or interpretations and can retain a source fragment ID.
Collection and sharing tools include list_study_collections,
create_study_collection, update_study_collection, delete_study_collection,
create_study_share_link, and revoke_study_share_link.
Asset relationships can be browsed with list_study_asset_links, created with
create_study_asset_link, and removed with delete_study_asset_link.
Fragments and their document hierarchy are available through
list_study_fragments and create_study_fragment.
MCP publication tools are get_study_publication, create_study_publication,
update_study_publication, and delete_study_publication.
Study bundles keep content and provenance while assigning new asset, fragment, annotation, knowledge-node, relation, and publication IDs on import. Existing same-named collections gain the imported asset as a member. Revocable share links are omitted because the token itself grants access and should not be copied into an archive.
Claude Code:
Claude Desktop (claude_desktop_config.json), or any MCP client:
Then ask for things in words: "plan my week from these notes and put it in
Toddyi", "what is overdue?", "mark the bank call done". Read-only tools
are annotated as such and delete_task as destructive, so a client can ask
before using it.
ChatGPT, Claude and Gemini
The remote server offers the everyday tools ? search, fetch, tasks,
folders, study materials, decks and the knowledge graph ? and needs nothing
installed. toddyi mcp here has the full set, Study editing included.
Releases
Pushing a tag v* runs .github/workflows/release.yml:
it tests, builds the CLI for every platform and the ChatGPT bundle, and
attaches them and SHA256SUMS to the release. A tag with a hyphen
(v0.2.0-rc.1) is published as a pre-release.
Layout
The server side is app/controllers/api/cli/ (the API),
app/controllers/features/cli/ (the approval page and the token list) and
app/models/features/accounts/cli_token.rb.
License
MIT. See LICENSE.
來源:README.md,提交 d342a43
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1- v0.2.7最新Oct 11, 2026

