DEPRECATED - ReOrc MCP Client

Client for ReOrc's Model Creation Platform (MCP).

Installation

Prerequisites

Before installing the ReOrc MCP Client, ensure you have the following:

1. Cursor IDE - Download and install from cursor.sh
2. Python 3.12 - Download from python.org or install via your system package manager
3. ReOrc Studio Account - Ensure you have access to ReOrc Studio with appropriate permissions

Installation Steps

1. Clone the Repository

git clone https://github.com/reorc/reorc-mcp.git
cd reorc-mcp

2. Install Dependencies

# Install required Python packages
pip install -r requirements.txt

The tool requires:

• requests>=2.28.0 - For API communication
• PyYAML>=6.0 - For YAML processing

3. Configure ReOrc Studio MCP Settings

1. Open ReOrc Studio in your browser
2. Click the user icon (bottom left corner)
3. Navigate to Profile → ReOrc MCP Settings
4. Copy the MCP Access Code (in JSON) from this page

4. Configure Cursor MCP Integration

1. Open Cursor IDE
2. Go to Settings (Cmd/Ctrl + Comma)
3. Navigate to Cursor Settings → Tools & Integrations → MCP Tools
4. Click New MCP Server, which opens a JSON file
5. Paste the JSON code from Step 3 above, and save
6. Cursor may notify registration of the new MCP, and ask for enabling (on bottom left)

5. Verify Installation

Test your installation by running:

# Validate your authentication
python3 cli.py auth validate

# If validation fails, login to get a new token
python3 cli.py auth login

Configuration File

The MCP configuration is stored in .cursor/mcp.json:

{
  "mcpServers": {
    "reorc-mcp": {
      "transport": "sse",
      "url": "https://mcp.test.reorc.cloud/mcp?access_token={YOUR_ACCESS_TOKEN}"
    }
  },
  "auth": {
    "defaultCredentials": {
      "email": "{YOUR_REORC_ACCOUNT}",
      "password": "{YOUR_REORC_PASSWORD}",
      "tenant_domain": "{TENANT_DOMAIN}"
    }
  }
}

Troubleshooting

If you encounter issues:

1. Authentication Problems: Run python3 cli.py auth validate to check your token
2. Missing Dependencies: Ensure all packages are installed with pip install -r requirements.txt
3. Python Version: Verify you're using Python 3.12 with python3 --version
4. Cursor Integration: Try refreshing the MCP server in Cursor settings

Getting Started

After completing the installation, you can start using ReOrc MCP Client directly within Cursor IDE. Here's a quick guide to get you up and running:

Quick Start Commands

Open Cursor IDE and use the chat interface to interact with ReOrc MCP. You can ask Cursor to:

1. List Available Projects

List all my ReOrc projects

2. Download a Project Locally

Download project "my_project_code" locally

3. Create a Data Model

Create a new staging model called "stg_customers" for project "my_project_code" that selects all customers from the raw customers table

4. Preview Data Model

Preview the data from model "stg_customers" in project "my_project_code"

5. Build Data Model

Build model "stg_customers" in project "my_project_code"

Example Workflow

1. Start a conversation in Cursor: Open Cursor's chat and ask to list your projects
2. Download a project: Ask Cursor to download the project you want to work on
3. Create models: Describe what kind of data model you want to create
4. Preview and iterate: Preview your models to see the data before building
5. Build and deploy: Build your models to make them available in your data warehouse

Video Tutorial

For a comprehensive walkthrough on building data foundations with ReOrc via Cursor, watch our tutorial video: 📺 Building Data Foundation with ReOrc via Cursor

Tips for Success

• Be descriptive: When asking Cursor to create models, describe your business logic clearly
• Use natural language: You don't need to know SQL - describe what you want in plain English
• Iterate locally: Use the local-first approach to make changes and test before syncing to the server
• Preview first: Always preview your models before building them to catch issues early

Overview

ReOrc MCP Client is a client-side application that interacts with the ReOrc Studio server while empowering users to take full control of model authoring, plan validation, and quality assurance in their local environment.

Local-First Development Model

This client implements a local-first approach to model development, allowing users to:

1. Create and modify models locally before syncing with the server
2. Track changes with Git for better version control and collaboration
3. Preview and validate plans before applying them
4. Roll back unwanted changes easily
5. Maintain transparency in how models are modified

Directory Structure

• local-model-projects/ - Downloaded DBT projects for local editing
• utils/ - Utilities for CLI operations using python3 to run
• .cursor/ - Configuration for Cursor IDE integration

CLI Usage

The client includes a command-line interface for working with local project files and Git repositories:

File Operations

# List files in a project
python3 cli.py file list dbt_project_1 [--path models/staging]

# Read a file
python3 cli.py file read dbt_project_1 models/staging/stg_customers.sql

# Write to a file
python3 cli.py file write dbt_project_1 models/staging/stg_orders.sql --content "SELECT * FROM orders"
# Or pipe content
cat new_model.sql | python3 cli.py file write dbt_project_1 models/staging/stg_orders.sql

# Delete a file
python3 cli.py file delete dbt_project_1 models/staging/deprecated_model.sql

Git Operations

# Initialize Git repository for a project
python3 cli.py git init dbt_project_1

# Check Git status
python3 cli.py git status dbt_project_1

# Commit changes
python3 cli.py git commit dbt_project_1 "Add new staging model for orders"

# Reset changes (soft reset by default)
python3 cli.py git reset dbt_project_1 
# Hard reset (discard all changes)
python3 cli.py git reset dbt_project_1 --hard
# Reset specific file
python3 cli.py git reset dbt_project_1 --file-path models/staging/stg_orders.sql

# View commit history
python3 cli.py git history dbt_project_1 --max-count 5

Project Operations

# Sync local changes to the server
python3 cli.py project sync dbt_project_1 --plan-id my_plan_name

# Sync specific models only
python3 cli.py project sync dbt_project_1 --plan-id my_plan_name --models stg_orders,stg_customers

# Automatically commit changes after syncing
python3 cli.py project sync dbt_project_1 --plan-id my_plan_name --commit

# Skip confirmation prompt
python3 cli.py project sync dbt_project_1 --plan-id my_plan_name --yes

MCP Server Connection

The client connects to the MCP server as configured in .cursor/mcp.json. This file contains:

{
  "mcpServers": {
    "reorc-mcp": {
      "transport": "sse",
      "url": "https://mcp.test.reorc.cloud/mcp?access_token={YOUR_ACCESS_TOKEN}"
    }
  },
  "auth": {
    "defaultCredentials": {
      "email": "{YOUR_REORC_ACCOUNT}",
      "password": "{YOUR_REORC_PASSWORD}",
      "tenant_domain": "{TENANT_DOMAIN}"
    }
  }
}

Complete End-to-End Workflow

1. Download and Initialize Project

# 1. Download the project files using CLI: 
python3 cli.py project download dbt_project_1

# 2. Extract the project files (happening automatically via CLI)

# 3. Initialize git repository in the project directory
python3 cli.py git init dbt_project_1

2. Create and Edit Models Locally

# Edit models using your preferred code editor
# OR use the CLI to write models:
python3 cli.py file write dbt_project_1 models/staging/stg_orders.sql --content "SELECT * FROM orders"

# Check status of your changes
python3 cli.py git status dbt_project_1

# Commit changes locally to track your work
python3 cli.py git commit dbt_project_1 "Update staging orders model"

3. Sync Changes to Server

# Sync all modified SQL models to the server
python3 cli.py project sync dbt_project_1 --plan-id my_plan_name

# Sync specific models and commit changes
python3 cli.py project sync dbt_project_1 --plan-id my_plan_name --models stg_orders --commit

4. Build and Test on Server

# In Cursor IDE: Call the build_data_model tool with your project_code and model_name

5. Roll Back if Needed

# Reset to the state before your changes using git
python3 cli.py git reset dbt_project_1 --hard

# Reset specific file only
python3 cli.py git reset dbt_project_1 --file-path models/staging/stg_orders.sql

Development Workflow Benefits

1. Local Development First

   • Edit files in your preferred editor
   • Use version control to track changes
   • Test locally before syncing to server

2. Transparent Change History

   • See what changes are being made with git diff
   • Track revision history locally
   • Maintain control over when to sync

3. Collaborative Workflow

   • Multiple developers can work on different models
   • Changes are easily reviewable as git history
   • Sync only when ready to integrate with server

4. Risk Mitigation

   • Roll back changes easily with git
   • Verify changes before syncing to server
   • Maintain local backups of all model versions

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

reorc-mcp-client