https://github.com/MammothGrowth/dbt-cli-mcp
DBT CLI MCP Server
https://github.com/MammothGrowth/dbt-cli-mcp
Last synced: about 2 months ago
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DBT CLI MCP Server
- Host: GitHub
- URL: https://github.com/MammothGrowth/dbt-cli-mcp
- Owner: MammothGrowth
- License: mit
- Created: 2025-03-17T00:59:05.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2025-04-10T19:49:47.000Z (2 months ago)
- Last Synced: 2025-04-10T20:47:06.182Z (2 months ago)
- Language: Python
- Size: 195 KB
- Stars: 6
- Watchers: 2
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-dbt - dbt-cli-mcp - MCP for dbt CLI. (Integrations)
- mcp-index - DBT CLI MCP Server - Wraps the dbt CLI tool to enable interaction with dbt projects for executing data transformation commands like run, test, and compile. Facilitates environment variable management and configurable paths for dbt execution. (Task and Project Management)
README
# DBT CLI MCP Server
A Model Context Protocol (MCP) server that wraps the dbt CLI tool, enabling AI coding agents to interact with dbt projects through standardized MCP tools.
## Features
- Execute dbt commands through MCP tools
- Support for all major dbt operations (run, test, compile, etc.)
- Command-line interface for direct interaction
- Environment variable management for dbt projects
- Configurable dbt executable path
- Flexible profiles.yml location configuration
## Installation
### Prerequisites
- Python 3.10 or higher
- `uv` tool for Python environment management
- dbt CLI installed
### Setup
```bash
# Clone the repository with submodules
git clone --recurse-submodules https://github.com/yourusername/dbt-cli-mcp.git
cd dbt-cli-mcp
# If you already cloned without --recurse-submodules, initialize the submodule
# git submodule update --init
# Create and activate a virtual environment
uv venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
# Install dependencies
uv pip install -e .
# For development, install development dependencies
uv pip install -e ".[dev]"
```
## Usage
### Command Line Interface
The package provides a command-line interface for direct interaction with dbt:
```bash
# Run dbt models
dbt-mcp run --models customers --project-dir /path/to/project
# Run dbt models with a custom profiles directory
dbt-mcp run --models customers --project-dir /path/to/project --profiles-dir /path/to/profiles
# List dbt resources
dbt-mcp ls --resource-type model --output-format json
# Run dbt tests
dbt-mcp test --project-dir /path/to/project
# Get help
dbt-mcp --help
dbt-mcp run --help
```
You can also use the module directly:
```bash
python -m src.cli run --models customers --project-dir /path/to/project
```
### Command Line Options
- `--dbt-path`: Path to dbt executable (default: "dbt")
- `--env-file`: Path to environment file (default: ".env")
- `--log-level`: Logging level (default: "INFO")
- `--profiles-dir`: Path to directory containing profiles.yml file (defaults to project-dir if not specified)
### Environment Variables
The server can also be configured using environment variables:
- `DBT_PATH`: Path to dbt executable
- `ENV_FILE`: Path to environment file
- `LOG_LEVEL`: Logging level
- `DBT_PROFILES_DIR`: Path to directory containing profiles.yml file
### Using with MCP Clients
To use the server with an MCP client like Claude for Desktop, add it to the client's configuration:
```json
{
"mcpServers": {
"dbt": {
"command": "uv",
"args": ["--directory", "/path/to/dbt-cli-mcp", "run", "src/server.py"],
"env": {
"DBT_PATH": "/absolute/path/to/dbt",
"ENV_FILE": ".env"
// You can also set DBT_PROFILES_DIR here for a server-wide default
}
}
}
}
```
## ⚠️ IMPORTANT: Absolute Project Path Required ⚠️
When using any tool from this MCP server, you **MUST** specify the **FULL ABSOLUTE PATH** to your dbt project directory with the `project_dir` parameter. Relative paths will not work correctly.
```json
// ❌ INCORRECT - Will NOT work
{
"project_dir": "."
}
// ✅ CORRECT - Will work
{
"project_dir": "/Users/username/path/to/your/dbt/project"
}
```
See the [complete dbt MCP usage guide](docs/dbt_mcp_guide.md) for more detailed instructions and examples.
## Available Tools
The server provides the following MCP tools:
- `dbt_run`: Run dbt models (requires absolute `project_dir`)
- `dbt_test`: Run dbt tests (requires absolute `project_dir`)
- `dbt_ls`: List dbt resources (requires absolute `project_dir`)
- `dbt_compile`: Compile dbt models (requires absolute `project_dir`)
- `dbt_debug`: Debug dbt project setup (requires absolute `project_dir`)
- `dbt_deps`: Install dbt package dependencies (requires absolute `project_dir`)
- `dbt_seed`: Load CSV files as seed data (requires absolute `project_dir`)
- `dbt_show`: Preview model results (requires absolute `project_dir`)
{
"models": "customers",
"project_dir": "/path/to/dbt/project",
"limit": 10
}
```
### dbt Profiles Configuration
When using the dbt MCP tools, it's important to understand how dbt profiles are handled:
1. The `project_dir` parameter **MUST** be an absolute path (e.g., `/Users/username/project` not `.`) that points to a directory containing both:
- A valid `dbt_project.yml` file
- A valid `profiles.yml` file with the profile referenced in the project
2. The MCP server automatically sets the `DBT_PROFILES_DIR` environment variable to the absolute path of the directory specified in `project_dir`. This tells dbt where to look for the profiles.yml file.
3. If you encounter a "Could not find profile named 'X'" error, it means either:
- The profiles.yml file is missing from the project directory
- The profiles.yml file doesn't contain the profile referenced in dbt_project.yml
- You provided a relative path instead of an absolute path for `project_dir`
Example of a valid profiles.yml file:
```yaml
jaffle_shop: # This name must match the profile in dbt_project.yml
target: dev
outputs:
dev:
type: duckdb
path: 'jaffle_shop.duckdb'
threads: 24
```
When running commands through the MCP server, ensure your project directory is structured correctly with both configuration files present.
## Development
### Integration Tests
The project includes integration tests that verify functionality against a real dbt project:
```bash
# Run all integration tests
python integration_tests/run_all.py
# Run a specific integration test
python integration_tests/test_dbt_run.py
```
#### Test Project Setup
The integration tests use the jaffle_shop_duckdb project which is included as a Git submodule in the dbt_integration_tests directory. When you clone the repository with `--recurse-submodules` as mentioned in the Setup section, this will automatically be initialized.
If you need to update the test project to the latest version from the original repository:
```bash
git submodule update --remote dbt_integration_tests/jaffle_shop_duckdb
```
If you're seeing errors about missing files in the jaffle_shop_duckdb directory, you may need to initialize the submodule:
```bash
git submodule update --init
```
## License
MIT