Mindwtr

Project Management

v26.11.1

Last updated Nov 2, 2026

n8n community node for managing Mindwtr tasks, projects, and subtasks via JSON file

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Included Nodes

Mindwtr

Description

Mindwtr node icon

n8n-nodes-mindwtr-file

Manage Mindwtr tasks, projects and subtasks from your n8n workflows —
no API, no credentials, just a plain JSON file.

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About ·
Installation ·
Getting started ·
Operations ·
Development

—

About

Mindwtr File is an n8n community node that turns a structured JSON document — the Mindwtr database — into a full task-management surface inside your workflows.

Instead of calling a remote service, the node reads the database from the data already flowing in your workflow (a file read from disk, S3, HTTP, a webhook payload…), applies the operation you selected, and hands the result back in the exact same shape — ready to be written straight back to a .json file.

Three resources — Task, Project and Subtask, with 16 operations in total.
Zero credentials — everything is processed locally in the workflow.
Cloud compatible — strict mode enabled, follows the n8n Cloud community-node rules.
Usable as a tool — plug the node directly into an AI Agent’s tool list.
Round-trip safe — whatever goes in comes back with the same structure, only the data is updated.
Human friendly — reference any item by its ID or by its name (Website Redesign, redesign, p1…).

—

Installation

Follow the official n8n community nodes guide:

1. Open Settings → Community Nodes in your n8n instance.
2. Select Install.
3. Enter @taistudio/n8n-nodes-mindwtr-file.
4. Accept the risk disclaimer and confirm Install.

Install from the command line

Docker / self-hosted default custom nodes folder
npm install @taistudio/n8n-nodes-mindwtr-file --prefix /home/node/.n8n
or, inside the n8n container
n8n install:community-node @taistudio/n8n-nodes-mindwtr-file

Then restart n8n and look for Mindwtr in the node panel.

—

Getting started

1 · The data format

The node operates on a Mindwtr JSON document. A minimal, complete example:

{
  "tasks": [
    {
      "id": "t3",
      "title": "Draft project proposal",
      "status": "next",
      "tags": ["urgent"],
      "contexts": ["@work"],
      "projectId": "p1",
      "dueDate": "2025-11-26T12:00:00.000Z",
      "createdAt": "2025-11-24T09:30:00.000Z",
      "updatedAt": "2025-11-24T09:30:00.000Z",
      "subtasks": [
        { "id": "st_1", "title": "Outline the goals", "status": "completed" }
      ]
    },
    {
      "id": "t1",
      "title": "Call Mom",
      "status": "inbox",
      "contexts": ["@home"]
    }
  ],
  "projects": [
    { "id": "p1", "title": "Website Redesign", "status": "active", "color": "#3b82f6" }
  ],
  "settings": {}
}

| Key | Required | Notes |
| ———– | :——: | ———————————————————— |
| tasks | ✅ | Every task needs an id and a title. |
| projects | ✅ | Every project needs an id and a title. |
| settings | ⬜ | Free-form object, preserved as-is when present. |
| subtasks | ⬜ | Nested inside their parent task. |
| projectId | ⬜ | Links a task to a project. |

> The node is tolerant about where the data sits: a top-level document, a { "data": … } wrapper (as returned by Extract From File), a bare list of tasks, or a single task are all detected automatically — up to 3 levels of nesting.

2 · The workflow pattern

flowchart LR
    A[["📄 data.json"]] --> B[Read Binary File]
    B --> C[Extract From File]
    C --> D{{"Mindwtr
create · update · delete
get many · validate"}}
    D --> E[Convert To File]
    E --> F[Write Binary Files]
    F --> G[["💾 data.json"]]

1. Read the JSON file into an n8n binary property (default: data).
2. Transform it with the Mindwtr node — create a task, update a project, validate a subtask…
3. Write the output back to a file with the next node. The JSON can be saved as-is, whatever operation was run.

3 · A concrete example

> “A webhook receives a new action item → store it in the Mindwtr file.”

| # | Node | Configuration |
| – | ———————— | ———————————————————————— |
| 1 | Webhook | POST /new-task, method POST |
| 2 | Mindwtr | Resource Task → Operation Create, Title ={{ $json.body.title }} |
| 3 | Convert To File | Operation To JSON |
| 4 | Write Binary Files | File Name data.json, Property data |

Every run appends the new task (with an auto-generated id and createdAt / updatedAt timestamps) and returns the whole updated database.

—

Output guarantees

Same shape in, same shape out

Every operation — including Get Many — returns data in the exact same JSON shape as the input:

the same top-level keys: a wrapper such as data (from Extract From File) stays in place, and the data is written back where it was found;
every extra key of the input (metadata, etc.) is kept untouched;
only the data itself (tasks, projects and settings) is updated;
settings is only present when the input had it;
data provided as a JSON string is handed back as a JSON string.

Get Many returns a filtered view

Get Many keeps that same shape, with the list reduced to the entries matching the filters and limit:

Failures never destroy your data

If an operation fails while Always Output Data is enabled, the input shape is preserved and an error key is added — a failed run never replaces your database with a bare error object.

—

Referencing items by ID or by name

Every field that expects an ID (task, project or subtask) also accepts the name as found in the JSON file:

So a failed run always doubles as a list of what’s available — no need to open the file to find the right reference.

From List pickers — every locator also offers a searchable From List mode, populated from the data present on the node’s input (100 entries per page, filterable as you type). If your data is nested, point the List Source option at the right property (default: ={{ $json }}, e.g. ={{ $json.data }} for an Extract From File payload).

—

Operations reference

Task

Project

Subtask

* required — leave it empty to auto-detect the item from the input data.

Statuses

Good to know

IDs and timestamps are automatic — new entries get a unique id (t…, p…, st_…) plus createdAt / updatedAt; every mutation refreshes updatedAt.
Deleting a project removes it and clears projectId on the tasks that referenced it.
One database per run — the database is parsed once from the first input item and shared, so several chained operations in a single run see each other’s changes.
No credentials required — the node only processes data already present in the workflow.

—

Compatibility

—

Development

Built with the official n8n-node CLI.

git clone https://github.com/TaiStudio/n8n-nodes-mindwtr-file.git cd n8n-nodes-mindwtr-file npm install

npm run dev # n8n with hot reload on http://localhost:5678 npm run build # compile to dist/ for distribution npm run lint # check code style (--fix to auto-fix) npm run release # build, lint, changelog, tag & publish to npm

Please read AGENTS.md and .agents/workflow.md before contributing.

—

Support & contributing

🐛 Bug reports & feature requests → open an issue
🔒 Security → see SECURITY.md
📦 Release notes → CHANGELOG.md
💖 Support the project → GitHub Sponsors · Buy Me a Coffee

—

Included Nodes

Description

n8n-nodes-mindwtr-file

About

Installation

Docker / self-hosted default custom nodes folder

or, inside the n8n container

Getting started

1 · The data format

2 · The workflow pattern

3 · A concrete example

Output guarantees

Same shape in, same shape out

Get Many returns a filtered view

Failures never destroy your data

Referencing items by ID or by name

Operations reference

Task

Project

Subtask

Statuses

Good to know

Compatibility

Development

Support & contributing

License

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