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cdmx-in
by cdmx-in
README.md
# Goodday MCP Server

A Model Context Protocol (MCP) server for integrating with Goodday project management platform. This server provides tools for managing projects, tasks, and users through the Goodday API v2.

## Features

### Project Management
- **get_projects**: Retrieve list of projects (with options for archived and root-only filtering)
- **get_project**: Get detailed information about a specific project
- **create_project**: Create new projects with customizable templates and settings
- **get_project_users**: Get users associated with a specific project

### Task Management
- **get_project_tasks**: Retrieve tasks from specific projects (with options for closed tasks and subfolders)
- **get_user_assigned_tasks**: Get tasks assigned to a specific user
- **get_user_action_required_tasks**: Get action-required tasks for a user
- **get_task**: Get detailed information about a specific task
- **get_task_details**: Get comprehensive task details including subtasks, custom fields, and full metadata
- **get_task_messages**: Retrieve all messages/comments for a specific task
- **create_task**: Create new tasks with full customization (subtasks, assignments, dates, priorities)
- **update_task_status**: Update task status with optional comments
- **add_task_comment**: Add comments to tasks

### Sprint Management
- **get_goodday_sprint_tasks**: Get tasks from specific sprints by project name and sprint name/number
- **get_goodday_sprint_summary**: Generate comprehensive sprint summaries with task details, status distribution, and key metrics

### User Management
- **get_users**: Retrieve list of organization users
- **get_user**: Get detailed information about a specific user

### Smart Query & Search
- **get_goodday_smart_query**: Natural language interface for common project management queries
- **search_goodday_tasks**: Semantic search across tasks using VectorDB backend
- **search_project_documents**: Search for documents within specific projects
- **get_document_content**: Retrieve full content of specific documents

## OpenWebUI Integration

This package also includes an OpenWebUI tool that provides a complete interface for Goodday project management directly in chat interfaces. The OpenWebUI tool includes:

### Features
- **Project Management**: Get projects, project tasks, and project details
- **Sprint Management**: Get tasks from specific sprints by name/number, comprehensive sprint summaries
- **User Management**: Get tasks assigned to specific users, user details
- **Task Details**: Get comprehensive task information including subtasks, custom fields, and metadata
- **Task Messages**: Retrieve all messages and comments for tasks
- **Smart Query**: Natural language interface for common project management requests
- **Semantic Search**: Search across tasks using VectorDB backend with embeddings
- **Document Management**: Search project documents and retrieve document content
- **Advanced Filtering**: Support for archived projects, closed tasks, subfolders, and more

### Setup
1. Copy `openwebui/goodday_openwebui_complete_tool.py` to your OpenWebUI tools directory
2. Configure the valves with your API credentials:
   - `api_key`: Your Goodday API token
   - `search_url`: Your VectorDB search endpoint (optional)
   - `bearer_token`: Bearer token for search API (optional)

### Vector Database Setup (Optional)
For semantic search functionality, you can set up a vector database using the provided n8n workflow (`openwebui/n8n-workflow-goodday-vectordb.json`). This workflow:
- Fetches all Goodday projects and tasks
- Extracts task messages and content
- Creates embeddings using Ollama
- Stores in Qdrant vector database
- Provides search API endpoint

See `openwebui/OPENWEBUI_TOOL_README.md` for detailed usage instructions.

## Installation

### From PyPI (Recommended)

```bash
pip install goodday-mcp
```

### From Source

#### Prerequisites
- Python 3.10 or higher
- UV package manager (recommended) or pip
- Goodday API token

#### Setup with UV

1. **Install UV** (if not already installed):
   ```bash
   curl -LsSf https://astral.sh/uv/install.sh | sh
   ```

2. **Clone and set up the project**:
   ```bash
   git clone https://github.com/cdmx1/goodday-mcp.git
   cd goodday-mcp
   
   # Create virtual environment and install dependencies
   uv venv
   source .venv/bin/activate  # On Windows: .venv\Scripts\activate
   uv sync
   ```

#### Setup with pip

```bash
git clone https://github.com/cdmx1/goodday-mcp.git
cd goodday-mcp
pip install -e .
```

### Configuration

1. **Set up environment variables**:
   Create a `.env` file in your project root or export the variable:
   ```bash
   export GOODDAY_API_TOKEN=your_goodday_api_token_here
   ```

   To get your Goodday API token:
   - Go to your Goodday organization
   - Navigate to Settings → API
   - Click the generate button to create a new token

## Usage

### Running the Server Standalone

If installed from PyPI:
```bash
goodday-mcp
```

If running from source with UV:
```bash
uv run goodday-mcp
```

### Using with Claude Desktop

1. **Configure Claude Desktop** by editing your configuration file:
   - **macOS**: `~/Library/Application Support/Claude/claude_desktop_config.json`
   - **Windows**: `%APPDATA%\Claude\claude_desktop_config.json`

2. **Add the server configuration**:

   **Option A: If installed from PyPI:**
   ```json
   {
     "mcpServers": {
       "goodday": {
         "command": "goodday-mcp",
         "env": {
           "GOODDAY_API_TOKEN": "your_goodday_api_token_here"
         }
       }
     }
   }
   ```

   **Option B: If running from source:**
   ```json
   {
     "mcpServers": {
       "goodday": {
         "command": "uv",
         "args": ["run", "goodday-mcp"],
         "env": {
           "GOODDAY_API_TOKEN": "your_goodday_api_token_here"
         }
       }
     }
   }
   ```

3. **Restart Claude Desktop** to load the new server.

### Using with Other MCP Clients

The server communicates via stdio transport and can be integrated with any MCP-compatible client. Refer to the [MCP documentation](https://modelcontextprotocol.io/) for client-specific integration instructions.

## API Reference

### Environment Variables

| Variable | Description | Required |
|----------|-------------|----------|
| `GOODDAY_API_TOKEN` | Your Goodday API token | Yes |

### Tool Examples

#### Get Projects
```python
# Get all active projects
get_projects()

# Get archived projects
get_projects(archived=True)

# Get only root-level projects
get_projects(root_only=True)
```

#### Create a Task
```python
create_task(
    project_id="project_123",
    title="Implement new feature",
    from_user_id="user_456",
    message="Detailed description of the task",
    to_user_id="user_789",
    deadline="2025-06-30",
    priority=5
)
```

#### Update Task Status
```python
update_task_status(
    task_id="task_123",
    user_id="user_456",
    status_id="status_completed",
    message="Task completed successfully"
)
```

## Data Formats

### Date Format
All dates should be provided in `YYYY-MM-DD` format (e.g., `2025-06-16`).

### Priority Levels
- 1-10: Normal priority levels
- 50: Blocker
- 100: Emergency

### Project Colors
Project colors are specified as integers from 1-24, corresponding to Goodday's color palette.

## Error Handling

The server includes comprehensive error handling:
- **Authentication errors**: When API token is missing or invalid
- **Network errors**: When Goodday API is unreachable
- **Validation errors**: When required parameters are missing
- **Permission errors**: When user lacks permissions for requested operations

All errors are returned as descriptive strings to help with troubleshooting.

## Development

### Project Structure
```
goodday-mcp/
├── goodday_mcp/         # Main package directory
│   ├── __init__.py      # Package initialization
│   └── main.py          # Main MCP server implementation
├── pyproject.toml       # Project configuration and dependencies
├── README.md           # This file
├── LICENSE             # MIT license
├── uv.lock            # Dependency lock file
└── .env               # Environment variables (create this)
```

### Adding New Tools

To add new tools to the server:

1. **Add the tool function** in `goodday_mcp/main.py` using the `@mcp.tool()` decorator:
   ```python
   @mcp.tool()
   async def your_new_tool(param1: str, param2: Optional[int] = None) -> str:
       """Description of what the tool does.
       
       Args:
           param1: Description of parameter 1
           param2: Description of optional parameter 2
       """
       # Implementation here
       return "Result"
   ```

2. **Test the tool** by running the server and testing with an MCP client.

### Testing

Test the server by running it directly:
```bash
# If installed from PyPI
goodday-mcp

# If running from source
uv run goodday-mcp
```

The server will start and wait for MCP protocol messages via stdin/stdout.

## Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

## License

This project is licensed under the MIT License - see the LICENSE file for details.

## Support

For issues related to:
- **MCP Server**: Create an issue in this repository
- **Goodday API**: Refer to [Goodday API documentation](https://www.goodday.work/developers/api-v2)
- **MCP Protocol**: Refer to [MCP documentation](https://modelcontextprotocol.io/)

## Changelog

### v1.1.0 (Current)
- **Enhanced Task Management**: Added `get_task_details` and `get_task_messages` for comprehensive task information
- **Sprint Management**: Added `get_goodday_sprint_tasks` and `get_goodday_sprint_summary` for sprint tracking
- **Smart Query Interface**: Added `get_goodday_smart_query` for natural language project queries
- **Semantic Search**: Added `search_goodday_tasks` with VectorDB integration for intelligent task search
- **Document Management**: Added `search_project_documents` and `get_document_content` for document handling
- **Improved Error Handling**: Enhanced error messages and status reporting
- **Advanced Filtering**: Support for archived projects, closed tasks, and subfolder inclusion

### v1.0.0
- Initial release
- Full project management capabilities
- Task management with comments and status updates
- User management
- Comprehensive error handling
- UV support with modern Python packaging

TDQS

B3.1/5.0

Scored across 21 tools

Disambiguation3/5

Most tools have distinct purposes, but there is notable overlap between get_task and get_task_details, and between get_project_tasks and get_goodday_sprint_tasks, which could cause confusion. Additionally, get_goodday_smart_query overlaps with several search and retrieval tools, though its natural language interface is a differentiating factor.

Naming Consistency4/5

The naming follows a consistent verb_noun pattern (e.g., create_project, get_task, update_task_status) with minor deviations like get_goodday_smart_query and search_goodday_tasks that include 'goodday' inconsistently. Overall, the pattern is clear and readable, with only slight inconsistencies.

Tool Count3/5

With 21 tools, the count is on the higher side for a project management server, bordering on heavy. While it covers many aspects, some tools might be redundant or could be consolidated, making it feel slightly bloated but still within a reasonable range for the domain.

Completeness4/5

The toolset provides comprehensive coverage for project and task management, including CRUD operations for projects, tasks, and comments, as well as retrieval for users, documents, and sprints. Minor gaps include lack of update/delete for projects and tasks, and no direct document creation tool, but core workflows are well-supported.

Maintenance

ActivityInactive
ResponsivenessNo issues