mcpField
D
dart-query

dart-query

Local
github.com/standardbeagleProductivity0Updated 13w ago

About dart-query

dart-query is an MCP server for managing Dart AI tasks and documents. Its DartQL selectors and server-side batch operations target many tasks in one call, with dry runs and CSV validation for safer bulk changes.

Key features

  1. 01DartQL task selectors
  2. 02Batch update and delete
  3. 03Single-task CRUD and search
  4. 04CSV import with validation
  5. 05Document management
  6. 06Dry runs and delete confirmation

Use cases

  1. 01Update tasks matching a selector
  2. 02Preview bulk changes before execution
  3. 03Create tasks from validated CSV
  4. 04Find and manage Dart AI documents

MCP support

Exposes Dart AI task and document operations to MCP clients, including DartQL-based batch tools, discovery, and workspace configuration.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"standardbeagle-dart-query": {
"command": "npx",
"args": [
"-y",
"@standardbeagle/dart-query"
],
"env": {
"DART_TOKEN": "<DART_TOKEN>"
}
}
}
}
Run commandnpx -y @standardbeagle/dart-query
Environment variables to set
DART_TOKENSecretYour Dart AI API token (get it from: https://app.dartai.com/?settings=account)

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npm@standardbeagle/dart-query0.3.5

Tools

24

Saved tool list · updated 2w ago

ParameterTypeRequiredDescription
levelenumNoDetail level: overview=categories, group=tools in category, tool=full documentationoverview | group | tool
targetstringNoGroup name (when level=group) or tool name (when level=tool)

Details

From the project README

dart-query

MCP server for Dart AI task management, optimized for batch operations and minimal context usage.

Instead of looping through tasks one-by-one (filling your context window with intermediate JSON), dart-query uses DartQL selectors and server-side batch operations to update hundreds of tasks in a single call. A 50-task update that would normally consume ~30K tokens takes ~200 tokens with zero context rot.

Quick Start

1. Get Your Dart AI Token

Visit https://app.dartai.com/?settings=account and copy your token (starts with dsa_).

2. Configure MCP

npx (recommended)

{
  "mcpServers": {
    "dart-query": {
      "command": "npx",
      "args": ["-y", "@standardbeagle/dart-query"],
      "env": {
        "DART_TOKEN": "dsa_your_token_here"
      }
    }
  }
}

SLOP-MCP (v0.10.0+)

slop register dart-query \
  --command npx \
  --args "-y" "@standardbeagle/dart-query" \
  --env DART_TOKEN=dsa_your_token_here \
  --scope user
3. Verify
info({ level: "overview" })
4. Example: Batch Update
// Preview first
batch_update_tasks({
  selector: "dartboard = 'Engineering' AND priority = 'high'",
  updates: { status: "Doing" },
  dry_run: true
})

// Execute
batch_update_tasks({
  selector: "dartboard = 'Engineering' AND priority = 'high'",
  updates: { status: "Doing" },
  dry_run: false
})

Tools

GroupToolsPurpose
Discoveryinfo, get_configExplore capabilities, workspace config
Task CRUDcreate_task, get_task, update_task, delete_task, add_task_commentSingle task operations
Querylist_tasks, search_tasksFind tasks with filters or full-text search
Batchbatch_update_tasks, batch_delete_tasks, get_batch_statusBulk operations with DartQL selectors
Importimport_tasks_csvBulk create from CSV with validation
Docslist_docs, create_doc, get_doc, update_doc, delete_docDocument management

See TOOLS.md for full parameter references, DartQL syntax, and CSV import format.

DartQL Selectors

SQL-92 WHERE clause syntax for targeting tasks in batch operations:

dartboard = 'Engineering' AND priority = 'high' AND tags CONTAINS 'bug'
due_at < '2026-01-18' AND status <> 'Done'
title LIKE 'Task%'                          -- starts with
title LIKE '%auth%'                         -- contains substring

Operators: =, !=, <>, >, >=, <, <=, LIKE, IN, NOT IN, BETWEEN, IS NULL, IS NOT NULL, CONTAINS Aliases: INCLUDES/HAS → CONTAINS · <> → != LIKE wildcards: % = any characters, _ = single character (case-insensitive)

Safety

All Dart AI operations are production (no sandbox). dart-query provides:

  • Dry-run mode on all batch operations — preview before executing
  • Validation phase for CSV imports — catch errors before creating anything
  • Confirmation flag (confirm: true) required for batch deletes
  • Recoverable deletes — tasks move to trash, not permanent deletion

License

MIT

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