Mindwtr

Mindwtr MCP Server

MCP server for Mindwtr. Connect MCP clients (Claude Desktop, etc.) to your local SQLite database, the desktop Local API, or a self-hosted Mindwtr Cloud endpoint.

By default this is a stdio server: MCP clients launch it as a subprocess and talk over JSON-RPC on stdin/stdout. It also has an opt-in HTTP transport (see Remote access (HTTP)) for self-hosters who want to expose it at a URL instead.

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App Binaries vs. MCP Helper

The desktop app includes a built-in MCP server in Settings → Integrations → MCP. It requires no separately installed runtime or helper. The desktop installer does not add a standalone mindwtr-mcp command to your PATH; mobile apps do not host MCP.

You do not need to run the whole app from source to use MCP. You can use the normal desktop app binary for your tasks, then run this separate MCP helper from the repository with Bun, or build the helper once and run it with Node. Point the helper at the desktop app's local mindwtr.db, or use the Local API backend below.

On desktop, the app shows the exact local data path in Settings -> Sync -> Local Data. Mobile binaries do not expose a local MCP server surface.

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Requirements

These requirements apply to the standalone helper, not the built-in desktop server.

• Node.js 20+ to run the helper. Prefer Node.js 22+ for prebuilt SQLite binaries on supported platforms; Node 20 requires a native build toolchain.
• Node-based SQLite mode uses the optional better-sqlite3 native addon. API-only installs can omit it with --omit=optional. If no prebuilt binary is available for your platform, npm needs a working C/C++ build toolchain and Python for node-gyp.
• Bun (recommended for development in this repo)
• A local database (mindwtr.db) for SQLite mode, a running desktop Local API and bearer token for API mode, or a self-hosted Mindwtr Cloud URL and bearer token for Cloud mode

For SQLite mode with npm 12, approve the SQLite dependency's install script; otherwise a successful install can still fail at startup with a missing native binding. For npx or global installs, allow only better-sqlite3:

npx --allow-scripts=better-sqlite3 -y mindwtr-mcp --db "/path/to/mindwtr.db"
npm install -g --allow-scripts=better-sqlite3 mindwtr-mcp

In MCP client configurations using npx, add "--allow-scripts=better-sqlite3" before "mindwtr-mcp" in args. For an existing project-local install, run npm install-scripts approve better-sqlite3, then npm rebuild better-sqlite3 from that project. Review the dependency before approving; do not enable all dependency scripts.

Default database locations. The installed Windows and macOS apps keep the database in a data subfolder from version 1.3.2 on; Linux and the portable builds are unchanged. The server looks in both places, so it finds the database either way.

• Linux: ~/.local/share/mindwtr/mindwtr.db (Flatpak: ~/.var/app/tech.dongdongbh.mindwtr/data/mindwtr/mindwtr.db)
• macOS, 1.3.2 and later: ~/Library/Application Support/mindwtr/data/mindwtr.db
• macOS, 1.3.1 and earlier: ~/Library/Application Support/mindwtr/mindwtr.db
• Windows, 1.3.2 and later: %APPDATA%\mindwtr\data\mindwtr.db
• Windows, 1.3.1 and earlier: %APPDATA%\mindwtr\mindwtr.db

Additional macOS paths for sandboxed builds:

• 1.3.2 and later: ~/Library/Containers/tech.dongdongbh.mindwtr/Data/Library/Application Support/mindwtr/data/mindwtr.db
• 1.3.1 and earlier: ~/Library/Containers/tech.dongdongbh.mindwtr/Data/Library/Application Support/mindwtr/mindwtr.db

A --db path pinned in an MCP client configuration keeps working across that move: if the file is not at the configured path, the server checks the matching data subfolder (or the parent folder) and reports on stderr which database it opened.

If mindwtr.db is missing but data.json exists in the same desktop data folder, the MCP server will bootstrap a fresh SQLite database from that local data snapshot on first start. Desktop Settings → Sync → Local Data shows the exact storage location used by the app.

You can override local mode with:

• --db /path/to/mindwtr.db
• MINDWTR_DB_PATH=/path/to/mindwtr.db
• MINDWTR_DB=/path/to/mindwtr.db

For self-hosted Cloud mode, use:

• --cloud-url https://mindwtr.example.com or MINDWTR_MCP_CLOUD_URL
• --cloud-token <token> or MINDWTR_MCP_CLOUD_TOKEN
• optional --cloud-allow-insecure-http=true for trusted private HTTP deployments

---

Start / Stop

Run from npm

After installing the published package, run it directly:

mindwtr-mcp --db "/path/to/mindwtr.db"

Or let an MCP client launch it through npx:

{
  "mcpServers": {
    "mindwtr": {
      "command": "npx",
      "args": [
        "-y",
        "mindwtr-mcp",
        "--db",
        "~/.local/share/mindwtr/mindwtr.db"
      ]
    }
  }
}

The npm package is read-only by default. Add --write only when you explicitly want add/update/complete/delete tools enabled.

Desktop Local API mode

Requires mindwtr-mcp 1.1.11 or later.

Enable the desktop app's Local API in Settings and copy its bearer token. Keep the app and API running. This backend uses the app's REST endpoints and never opens a database or falls back to SQLite.

For an API-only installation, omit the optional native SQLite addon:

npm install -g --omit=optional mindwtr-mcp

Configure your MCP client to pass the token through its environment, rather than putting it in command-line arguments:

{
  "command": "mindwtr-mcp",
  "args": ["--api-url", "http://127.0.0.1:3456"],
  "env": {
    "MINDWTR_MCP_API_TOKEN": "<token from desktop settings>"
  }
}

Use the port shown in Settings. MINDWTR_MCP_API_URL can replace --api-url. URLs must use literal 127.0.0.1 or [::1], with no credentials, path, query or fragment; redirects are refused. Do not combine API and Cloud/--db options. Existing database-path environment variables are ignored in API mode.

Writes remain disabled unless explicitly enabled with --write. If the app is closed or the token is invalid, the helper returns an error. A timed-out write may have reached the app: inspect the task before retrying, as the helper does not retry writes automatically.

MCP capability	Desktop Local API support
List/get tasks	Supported, including rich search operators, date filters, sorting and pagination
Create tasks	Explicit title and fields; quickAdd is unavailable
Update/complete/delete/restore tasks	Supported through the API's corresponding endpoints; terminal status changes cannot be submitted as ordinary edits
List/get/create/update/delete projects	Supported for the API's basic project fields: title, color, status, Area and sequential behavior
List areas	Supported
Sections, managed people, Area writes	Unavailable; these tools are hidden in API mode
GTD availability view	Unavailable because the API does not expose the required section snapshot
Replacing attachment links	Unavailable because the API does not provide conditional attachment updates

Other unsupported fields are rejected before a write. The desktop API's recurrence limitations also apply; some recurring completions must be performed in the app. This backend does not promise full SQLite/Cloud tool parity.

--api-url selects the helper's data source. --http instead selects how an MCP client connects to the helper; it can be used with any backend and has a separate authentication token.

Self-hosted Cloud mode

Use Cloud mode when you run your own Mindwtr Cloud server and want MCP tools without pointing the helper at a local SQLite database:

npx -y mindwtr-mcp \
  --cloud-url "https://mindwtr.example.com" \
  --cloud-token "$MINDWTR_TOKEN"

Or pass the same values through environment variables:

MINDWTR_MCP_CLOUD_URL="https://mindwtr.example.com" \
MINDWTR_MCP_CLOUD_TOKEN="$MINDWTR_TOKEN" \
npx -y mindwtr-mcp

Cloud mode uses the self-hosted Cloud API. Reads come from the current /v1/data snapshot; with --write, task/project/section/area writes go through the Cloud server's per-resource REST endpoints (POST /v1/tasks, PATCH /v1/tasks/:id, and so on), so they get the same validation and revision stamping as any other client. Without --write, write tools return read_only. Person edits and restoring deleted tasks are not available in Cloud mode yet.

This does not make Mindwtr Cloud itself a hosted MCP server. It is still the same stdio helper, backed by a Cloud URL that you operate.

For private HTTP test deployments, local/private HTTP URLs are allowed by the shared Cloud client rules. Use --cloud-allow-insecure-http=true only for a self-hosted endpoint you intentionally trust.

Remote access (HTTP)

By default mindwtr-mcp only speaks stdio. Pass --http to also (instead of stdio) serve a stateless streamable-HTTP MCP endpoint, so you can point a remote MCP client at a URL — the motivating case is Gemini Spark "custom apps", which take an MCP server URL. HTTP mode works with all three backends.

mindwtr-mcp --http --http-token "$(openssl rand -hex 32)" --db "/path/to/mindwtr.db"

Flags (all have MINDWTR_MCP_HTTP* env var equivalents):

• --http / MINDWTR_MCP_HTTP — enable HTTP mode. Also implied by setting --http-host, --http-port, or --http-token.
• --http-token <token> / MINDWTR_MCP_HTTP_TOKEN — required whenever HTTP mode is on, at least 16 characters. Generate one with openssl rand -hex 32. The server refuses to start without it — there is no way to expose HTTP mode unauthenticated, even on loopback.
• --http-host <host> / MINDWTR_MCP_HTTP_HOST — bind address, default 127.0.0.1.
• --http-port <port> / MINDWTR_MCP_HTTP_PORT — bind port, default 8722.

The MCP endpoint is POST /mcp and requires Authorization: Bearer <token> on every request; GET /healthz returns 200 ok without auth for reverse-proxy health checks. Requests without a valid token get 401; repeated authentication failures get 429 with a Retry-After header. Bodies over 1 MiB get 413. When HTTP mode is on, the server does not also connect a stdio transport — it stays alive as long as the HTTP server is listening, not stdin.

There is no built-in TLS termination or rate limiting for authenticated requests. If you're exposing this beyond localhost, put a reverse proxy (e.g. Caddy, nginx) in front for TLS and put the resulting https:// URL (plus your token) into the remote MCP client.

Run directly from the repo

# from repo root (read-only by default)
bun run mindwtr:mcp -- --db "/path/to/mindwtr.db"

Enable writes (required for add/update/complete/delete tools):

bun run mindwtr:mcp -- --db "/path/to/mindwtr.db" --write

Stop:

• Press Ctrl+C in the terminal.

Keep-alive behavior (why it sometimes exits)

The MCP server is stdio‑based. It stays alive as long as stdin is open. If your shell/client closes stdin, the process exits.

To force an immediate exit when stdin closes (no keep-alive), pass --nowait:

bun run mindwtr:mcp -- --db "/path/to/mindwtr.db" --nowait

Note: When an MCP client launches the server, it keeps stdin open, so the server should remain connected.

Run without the helper script

bun run --filter mindwtr-mcp dev -- --db "/path/to/mindwtr.db"

Stop:

• Press Ctrl+C in the terminal.

Build and run the binary entry (Node)

# from repo root
bun run --filter mindwtr-mcp build
node apps/mcp-server/dist/cli.js --db "/path/to/mindwtr.db"

Stop:

• Press Ctrl+C in the terminal.

---

Why mindwtr-mcp is “command not found”

mindwtr-mcp is the package binary. It exists after installing the npm package globally, after an MCP client launches it through npx, or after you build the source package and run it with Node.

Use one of these source-tree options instead:

# ✅ works immediately
bun run mindwtr:mcp -- --db "/path/to/mindwtr.db"

# ✅ build then run
bun run --filter mindwtr-mcp build
node apps/mcp-server/dist/cli.js --db "/path/to/mindwtr.db"

Optional: create a global mindwtr-mcp command

If you want a real mindwtr-mcp command on your PATH, create a tiny wrapper:

cat > ~/bin/mindwtr-mcp <<'EOF'
#!/usr/bin/env bash
set -euo pipefail
cd /absolute/path/to/Mindwtr
exec bun run mindwtr:mcp -- "$@"
EOF
chmod +x ~/bin/mindwtr-mcp

Then use:

mindwtr-mcp --db "/path/to/mindwtr.db"

Desktop app toggle?

The desktop app has Settings → Integrations → MCP. Access is disabled and read-only by default. Enable it and copy connection details for a client supporting authenticated Streamable HTTP at http://127.0.0.1:8722/mcp. Configuration syntax depends on the client; stdio-only clients can continue using this standalone helper.

Enable Allow changes only to permit creating, editing, and deleting tasks and projects, including completing tasks. Connected AI clients can read exposed Mindwtr data and may send it to their provider. Keep the copied bearer token private; regenerating it disconnects old clients.

The built-in server runs inside the desktop app and shares its task and project operations with the Local API. You do not need to enable the Local API. Closing to the tray keeps it running; disabling MCP or quitting stops it. A startup failure or occupied port is shown in Settings with Retry. The app must stay available. This mode does not provide remote ChatGPT access, a tunnel, or hosting, and has the same supported operations as the Local API backend above.

Source builds compile the built-in server with the desktop Rust application; no separate MCP executable or runtime is bundled.

---

MCP Client Configuration

MCP clients run the server as a subprocess. You point them to the command and pass args/env.

Important: Do NOT use bun run mindwtr:mcp for MCP clients. The bun run wrapper outputs shell messages to stdout (e.g., $ bun run --filter...) which breaks the JSON-RPC protocol. Always run bun directly on the source file.

Example (generic MCP config)

{
  "mcpServers": {
    "mindwtr": {
      "command": "bun",
      "args": [
        "/absolute/path/to/Mindwtr/apps/mcp-server/src/cli.ts",
        "--db",
        "~/.local/share/mindwtr/mindwtr.db"
      ]
    }
  }
}

Add --write to the args if you want to enable add/update/complete/delete tools.

If your client doesn't support Bun, build first and use Node:

# Build once
cd /path/to/Mindwtr && bun run --filter mindwtr-mcp build

{
  "mcpServers": {
    "mindwtr": {
      "command": "node",
      "args": [
        "/absolute/path/to/Mindwtr/apps/mcp-server/dist/cli.js",
        "--db",
        "~/.local/share/mindwtr/mindwtr.db"
      ]
    }
  }
}

Add --write to the args if you want to enable add/update/complete/delete tools.

Claude Desktop

Claude Desktop supports MCP (stdio). Add a server entry in its MCP configuration.

Typical config file locations:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

After editing, fully quit and relaunch Claude Desktop.

Claude Code (CLI)

Add a server via the CLI:

claude mcp add mindwtr -- \
  bun /path/to/Mindwtr/apps/mcp-server/src/cli.ts --db "/path/to/mindwtr.db" --write

Or edit ~/.claude.json directly:

{
  "projects": {
    "/path/to/your/project": {
      "mcpServers": {
        "mindwtr": {
          "type": "stdio",
          "command": "bun",
          "args": [
            "/absolute/path/to/Mindwtr/apps/mcp-server/src/cli.ts",
            "--db",
            "~/.local/share/mindwtr/mindwtr.db",
            "--write"
          ]
        }
      }
    }
  }
}

Then restart the Claude Code session and run /mcp to verify it's connected.

OpenAI Codex (config.toml)

Codex stores MCP config in ~/.codex/config.toml. Add:

[mcp_servers.mindwtr]
command = "bun"
args = ["/absolute/path/to/Mindwtr/apps/mcp-server/src/cli.ts", "--db", "/path/to/mindwtr.db", "--write"]

# Optional: pass env vars to the server
[mcp_servers.mindwtr.env]
MINDWTR_DB_PATH = "/path/to/mindwtr.db"

Restart Codex after saving.

Gemini CLI

Gemini CLI uses a JSON settings.json with mcpServers, either:

• User scope: ~/.gemini/settings.json
• Project scope: .gemini/settings.json in your repo

You can add Mindwtr MCP two ways:

1) CLI (recommended):

gemini mcp add mindwtr \
  bun /absolute/path/to/Mindwtr/apps/mcp-server/src/cli.ts \
  --db "/path/to/mindwtr.db" --write

2) Edit settings.json manually:

{
  "mcpServers": {
    "mindwtr": {
      "command": "bun",
      "args": ["/absolute/path/to/Mindwtr/apps/mcp-server/src/cli.ts", "--db", "/path/to/mindwtr.db", "--write"]
    }
  }
}

Restart the Gemini CLI session after saving.

Other MCP clients

Any MCP-compatible client can work as long as it can launch a stdio server with the command + args above.

---

Migration: tool rename (mindwtr.* → mindwtr_*)

Breaking change (introduced in this release): all tool names have changed from dot-notation (mindwtr.list_tasks) to underscore-notation (mindwtr_list_tasks) to comply with MCP client validation rules (e.g. Claude Desktop).

Old → new mapping:

Old name	New name
mindwtr.list_tasks	mindwtr_list_tasks
mindwtr.list_projects	mindwtr_list_projects
mindwtr.get_project	mindwtr_get_project
mindwtr.get_task	mindwtr_get_task
mindwtr.list_areas	mindwtr_list_areas
mindwtr.add_task	mindwtr_add_task
mindwtr.update_task	mindwtr_update_task
mindwtr.complete_task	mindwtr_complete_task
mindwtr.delete_task	mindwtr_delete_task
mindwtr.restore_task	mindwtr_restore_task
mindwtr.add_project	mindwtr_add_project
mindwtr.update_project	mindwtr_update_project
mindwtr.delete_project	mindwtr_delete_project
mindwtr.add_area	mindwtr_add_area
mindwtr.update_area	mindwtr_update_area
mindwtr.delete_area	mindwtr_delete_area

Upgrade action: find and replace mindwtr. with mindwtr_ in any MCP client configs, system prompts, scripts, or automations that reference these tool names. No other changes are required.

---

Tools

• mindwtr_list_tasks
  • Input: { status?, projectId?, includeDeleted?, limit?, offset?, search?, dueDateFrom?, dueDateTo?, isFocusedToday?, view?, sortBy?, sortOrder? }
  • view narrows by GTD availability: available, deferred or blocked
• mindwtr_list_projects
  • Input: {}
• mindwtr_get_project
  • Input: { id, includeDeleted? }
• mindwtr_list_sections
  • Input: { projectId?, includeDeleted? }
• mindwtr_get_section
  • Input: { id, includeDeleted? }
• mindwtr_list_areas
  • Input: {}
• mindwtr_list_people
  • Input: { includeDeleted? }
• mindwtr_get_person
  • Input: { id, includeDeleted? }
• mindwtr_get_task
  • Input: { id, includeDeleted? }
• mindwtr_add_task (requires --write)
  • Input: { title? | quickAdd?, status?, projectId?, sectionId?, areaId?, dueDate?, startTime?, cancelledAt?, reviewAt?, recurrence?, contexts?, tags?, description?, priority?, energyLevel?, assignedTo?, timeEstimate?, taskMode?, relativeStartOffset?, showFutureRecurrence?, pushCount?, checklist?, textDirection?, location?, isFocusedToday?, timeSpentMinutes?, suppressMindwtrReminders?, repeatReminderMinutes?, attachments? }
• mindwtr_update_task (requires --write)
  • Input: { id, title?, status?, projectId?, sectionId?, areaId?, dueDate?, startTime?, cancelledAt?, reviewAt?, recurrence?, contexts?, tags?, description?, priority?, energyLevel?, assignedTo?, timeEstimate?, taskMode?, relativeStartOffset?, showFutureRecurrence?, pushCount?, checklist?, textDirection?, location?, isFocusedToday?, timeSpentMinutes?, suppressMindwtrReminders?, repeatReminderMinutes?, order?, boardOrder?, focusOrder?, attachments? }
  • recurrence accepts a recurrence object or an RFC 5545 RRULE string. Pass null to clear it.
  • attachments holds link attachments only ({ id?, title?, uri }, e.g. obsidian://, file:// or https://). The list you pass is the complete set of links: links you leave out are removed, file attachments are never touched, and null clears every link.
  • cancelledAt is an ISO timestamp with timezone. Setting it closes the task as cancelled (archived) without counting it as completed or generating its next recurrence. Moving it to an active status or completing it clears cancellation. Update every syncing client before using cancellation; older writers can discard the marker.
• mindwtr_complete_task (requires --write)
  • Input: { id }
• mindwtr_delete_task (requires --write)
  • Input: { id }
• mindwtr_restore_task (requires --write)
  • Input: { id }
• mindwtr_add_project (requires --write)
  • Input: { title, color?, status?, areaId?, isSequential?, isFocused?, dueDate?, startDate?, cancelledAt?, reviewAt?, supportNotes?, attachments? }
• mindwtr_update_project (requires --write)
  • Input: { id, title?, color?, status?, areaId?, isSequential?, isFocused?, dueDate?, startDate?, cancelledAt?, reviewAt?, supportNotes?, attachments? }
  • attachments follows the same rule as mindwtr_update_task: link attachments only, the list is the complete set of links, and null clears them.
• mindwtr_delete_project (requires --write)
  • Input: { id }
• mindwtr_add_section (requires --write)
  • Input: { projectId, title, description?, order?, isCollapsed? }
• mindwtr_update_section (requires --write)
  • Input: { id, title?, description?, order?, isCollapsed? }
• mindwtr_delete_section (requires --write)
  • Input: { id }
• mindwtr_add_area (requires --write)
  • Input: { name, color?, icon? }
• mindwtr_update_area (requires --write)
  • Input: { id, name?, color?, icon? }
• mindwtr_delete_area (requires --write)
  • Input: { id }
• mindwtr_add_person (requires --write)
  • Input: { name, note?, referenceLink? }
• mindwtr_update_person (requires --write)
  • Input: { id, name?, note?, referenceLink? }
• mindwtr_rename_person (requires --write)
  • Input: { id, name, updateTasks? }
• mindwtr_delete_person (requires --write)
  • Input: { id }

All tools return JSON text payloads with the resulting task, project, section, area, person, or collection payload.

---

Testing

Quick smoke test (CLI)

1. Start the server (read‑only):

bun run mindwtr:mcp -- --db "~/.local/share/mindwtr/mindwtr.db"

2. Connect via your MCP client and run:

• mindwtr_list_tasks (limit 5)

If you want to test writes, restart with --write:

bun run mindwtr:mcp -- --db "~/.local/share/mindwtr/mindwtr.db" --write

Then test:

• mindwtr_add_task (quickAdd: "Test task @home /due:tomorrow")
• mindwtr_complete_task (use returned task id)
• mindwtr_update_task (e.g. set status or dueDate)
• mindwtr_delete_task (use returned task id)
• mindwtr_get_task (use returned task id)
• mindwtr_restore_task (after delete, restore the task)
• mindwtr_list_projects
• mindwtr_get_project (use returned project id)
• mindwtr_list_areas
• mindwtr_list_people
• mindwtr_add_project
• mindwtr_update_project
• mindwtr_delete_project
• mindwtr_add_area
• mindwtr_update_area
• mindwtr_delete_area
• mindwtr_add_person
• mindwtr_update_person
• mindwtr_rename_person
• mindwtr_get_person (use returned person id)
• mindwtr_delete_person
• mindwtr_list_tasks with dueDateFrom, dueDateTo, sortBy, sortOrder

If the list returns tasks and add/complete works, the server is healthy.

Stdio JSON-RPC E2E (transport validation)

Use any MCP client or a small script to send:

• initialize
• notifications/initialized
• tools/list
• tools/call (e.g. mindwtr_list_projects or mindwtr_list_tasks)

If these succeed, the stdio transport is working end-to-end.

Claude Code sanity check

1. Add the server:

claude mcp add mindwtr -- \
  bun /path/to/Mindwtr/apps/mcp-server/src/cli.ts --db "/path/to/mindwtr.db" --write

2. Restart Claude Code, run /mcp, and verify mindwtr is connected.
3. Ask the model to call:
   • mindwtr_list_tasks (limit 5)
   • mindwtr_add_task (quickAdd: "Test MCP @home /due:tomorrow")
   • mindwtr_complete_task (use returned id)

---

Safety & Concurrency

The SQLite details below apply to direct database mode. Local API mode uses the desktop app's native handlers, and Cloud mode uses the self-hosted server.

• The server uses SQLite WAL mode. Read-only tools can run while the desktop app is open.
• Write tools fail fast on SQLite writer locks, then retry the whole Mindwtr write operation. Each retry reloads current data before applying the requested change, so a delayed MCP write does not keep working from a stale pre-lock snapshot.
• Writes are disabled by default. Use --write to enable edits.
• Write operations go through the shared @mindwtr/core store to enforce business rules (both Bun and Node).
• SQL is reserved for read-heavy paths (list/search) where performance matters.
• Do not point a separate container/server deployment at the same local storage or sync data while the desktop app is also writing. That creates independent writers outside the local SQLite coordination path and is unsupported.

---

Notes

• This MCP server targets the SQLite database used by the desktop app, with mutations routed through @mindwtr/core.
• Keep an eye on schema changes across app versions (update queries if needed).