Dart Context Orchestration Endpoint

An implementation of the Model Context Protocol (MCP) server designed for the Dart ecosystem, offering comprehensive services for commitment tracking, digital asset administration, and organizational structuring through defined MCP interfaces.

Prerequisites for Deployment

• Runtime environment compatible with Node.js (version 16.x or newer)
• Python interpreter (version 3.8 or higher)
• The Dart Python SDK must be installed (pip install dart-sdk)
• A valid authorization credential for the Dart API

Core Capabilities

• Commitment Lifecycle Oversight
• Instantiation and modification of work items
• Designation of urgency levels and operational states
• Allocation of responsibilities to team members
• Digital Artifact Administration
• Provisioning and systematic arrangement of documents
• Native support for Markdown formatting
• Generation of summary reports
• Environment Structuring
• Initialization and governance of logical workspaces
• Hierarchical organization of content via directories
• Management of access control policies
• Dartboard Interoperability
• Standardized state enumeration handling
• Hierarchical content indexing
• Facilitation of team coordination mechanisms

Deployment Procedures

Automated Installation via Smithery

To integrate the Dart Context Orchestration Endpoint into Claude Desktop using Smithery:

bash npx -y @smithery/cli install @jmanhype/dart-mcp-server --client claude

Manual Setup

1. Obtain a copy of the repository: bash git clone https://github.com/jmanhype/dart-mcp-server.git cd dart-mcp-server

2. Resolve Node.js dependencies: bash npm install

3. Configure the Python environment and load the Dart SDK: bash

Establish and activate isolated environment

python -m venv .venv source .venv/bin/activate # On Windows: .venv\Scripts\activate

Install Dart SDK component

pip install dart-sdk

1. Define necessary configuration parameters: bash

Replicate example configuration file

cp .env.example .env

Edit .env to supply required parameters

Essential: DART_TOKEN

Optional: PYTHONPATH (location of Dart SDK)

Execution Guide

1. Compile the TypeScript source code: bash npm run build

2. Initiate the MCP server instance: bash npm start

Development Workflow

bash

Monitor TypeScript source files for changes

npm run dev

Execute verification suites

npm test

Required Environment Variables

Ensure a .env file is present with the following definitions:

env

Mandatory: Your authenticated Dart API credential

DART_TOKEN=your_dart_token_here

Recommended: Directory pointing to your Dart SDK installation

PYTHONPATH=/path/to/dart/sdk

Optional: Explicit path to the Python interpreter (defaults to system path)

PYTHON_PATH=/path/to/python

Exposed MCP Functionality

This gateway exposes the following interoperability functions: - create_task: Initiate new commitments, specifying attributes like designation, description, criticality, etc. - update_task: Modify parameters of existing commitments (status, nomenclature, details) - get_default_status: Retrieve identifiers (DUIDs) for system default statuses - get_default_space: Fetch the identifier (DUID) for the primary organizational space - get_dartboards: Enumerate available Dartboard contexts - get_folders: List sub-containers within a specified organizational space - create_folder: Provision new organizational units - create_doc: Generate new documentation artifacts or analytical reports - create_space: Establish new high-level organizational containers - delete_space: Permanently remove existing high-level organizational containers

Error Resolution

If operational hurdles arise:

1. Validate Python environment integrity: bash python --version pip list | grep dart

2. Confirm Dart SDK integrity via execution: python python -c "import dart; print(dart.version)"

3. Verify environment variable accessibility: bash echo $DART_TOKEN echo $PYTHONPATH

Licensing

MIT License

Dart Infrastructure Utilities

Package Index Supported Python Versions License

Dart facilitates project oversight driven by artificial intelligence.

dart-tools constitutes the Dart Command Line Interface alongside its Python Library component. This enables direct interfacing with the Dart platform via terminal commands or Python scripting.

• Setup Instructions
• Command Line Usage Guide
• Utilizing the Python Library
• Python Library Integration within AWS Lambda Environments
• Interacting with the MCP Server Component
• Advanced Operational Scenarios
• Support Channels and Documentation
• Contribution Guidelines
• Licensing Terms

Setup

In your command-line interface, install via:

bash pip install dart-tools

Command Line Interaction

Commence by establishing authorization credentials using:

bash dart login

Subsequently, you can generate a new commitment with a directive similar to:

bash dart createtask "Finalize marketing copy" -p0 --tag communications

This command initiates a new item titled 'Finalize marketing copy' assigned 'Urgent' priority (P0) and tagged as 'communications'.

You can survey all available parameters and options using dart --help or the context-specific help, for instance, dart createtask --help.

A frequent supplemental procedure involves revising an extant commitment. To achieve this, execute a command structured as:

bash dart updatetask [DUID] -s Completed

This instruction marks the targeted commitment as 'Completed'. Replace [DUID] (including the brackets) with the actual 'Dart ID' of the desired item. A DUID can be retrieved through multiple means, such as copying it from the concluding segment of a task's web address or selecting 'Copy ID' from the options menu under the '...' icon on the task's detail view within Dart.

Python Library Integration

Initially, configure authentication. Execute dart login in the terminal for an interactive session, or alternatively, navigate to your Dart profile dashboard and invoke dart.login(token) or persist the token within the DART_TOKEN environment variable.

Then, script execution can proceed as follows:

python import os from dart import create_task, is_logged_in, update_task

Validate authentication setup and halt if missing (removable after full configuration)

is_logged_in(should_raise=True)

Instantiate a new commitment: 'Finalize marketing copy', Priority 'Urgent' (p0), Tag 'communications'

new_commitment = create_task( "Finalize marketing copy", priority_int=0, tag_titles=["communications"] )

Transition the commitment state to 'Completed'

update_task(new_commitment.duid, status_title="Completed")

Interacting via the MCP Server

The Model Context Protocol (MCP) server serves as the bridge enabling sophisticated AI entities (such as Claude) to interface with Dart through standardized operational tools. This framework ensures fluid integration of AI processing capabilities with Dart's structured commitment management system.

Deployment Steps

bash

Clone the source repository

git clone https://github.com/its-dart/dart-tools.git cd dart-tools/dart/mcp

Install prerequisite packages

npm install

Establish Python execution context

python -m venv .venv source .venv/bin/activate # On Windows: .venv\Scripts\activate pip install dart-tools

Configure operational parameters

cp .env.example .env

Populate .env with your DART_TOKEN value

Available MCP Interfaces

The gateway exposes the following functional interfaces: - Commitment Administration (creation/modification) - Artifact Management (document generation/structuring) - Space Governance (workspace setup/folder organization) - Dartboard Context Access

Refer to the MCP Server README for comprehensive interface specifications.

Advanced Functionality

Nearly all operations possible within the native Dart environment are achievable via the Python library, though convenience wrappers may not exist for every scenario. For complex undertakings, direct consultation with the development team is recommended for support.

However, for self-directed exploration, the client library is strongly typed, allowing introspection into available methods. All state modifications are channeled exclusively through the dart.transact method.

For instance, mimicking the functionality of update_task can be accomplished using:

python from dart import ( Dart, Operation, OperationKind, OperationModelKind, TaskUpdate, TransactionKind, )

Initialize the underlying transactional client

dart = Dart()

Construct the necessary modification payload

task_update = TaskUpdate( duid="[DUID]", size=5, ) task_update_op = Operation( model=OperationModelKind.TASK, kind=OperationKind.UPDATE, data=task_update, )

Invoke the transaction to commit the modification

response = dart.transact([task_update_op], TransactionKind.TASK_UPDATE)

Support and Documentation

• Portal Link
• Web Application Access
• Assistance Center
• Reporting Defects and Feature Requests
• Source Code Repository
• Discord Community Channel
• Contact Email: support@itsdart.com

Contributions

We welcome community contributions! Please initiate a new issue or submit a pull request.

Licensing

This software is distributed under the MIT License.

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