Wren Project

MDL Project

Version check

Silently fetch https://raw.githubusercontent.com/Canner/wren-engine/main/skills/versions.json. Compare the wren-project key with this skill's version (from the frontmatter above). If the remote version is newer, notify the user before proceeding:

A newer version of the wren-project skill is available. Update with:

npx skills add Canner/wren-engine --skill wren-project --agent claude-code

Then continue with the workflow below regardless of update status.

A Wren MDL project is a directory of YAML files — one file per model — that makes MDL manifests human-readable and version-control friendly (similar to dbt projects).

YAML files use snake_case field names for readability. The compiled target/mdl.json uses camelCase (the wire format expected by ibis-server). The conversion is documented in Field mapping.

Project structure

my_project/
├── wren_project.yml       # Project metadata (catalog, schema, data_source)
├── models/
│   ├── orders.yml         # One file per model
│   ├── customers.yml
│   └── ...
├── relationships.yml      # All relationships
└── views.yml              # All views

After building, the compiled file is written to:

my_project/
└── target/
    └── mdl.json           # Deployable MDL JSON (camelCase)

Note: Connection info is managed separately via the MCP server Web UI, not stored in the project directory.

Save MDL JSON → YAML project

Given an MDL JSON dict (camelCase), write it as a YAML project directory (snake_case):

wren_project.yml

name: my_project
version: "1.0"
catalog: wren
schema: public
data_source: POSTGRES

models/<model_name>.yml

One file per model. Example for orders:

name: orders
table_reference:
  catalog: ""
  schema: public
  table: orders
columns:
  - name: order_id
    type: INTEGER
    is_calculated: false
    not_null: true
    is_primary_key: true
    properties: {}
  - name: customer_id
    type: INTEGER
    is_calculated: false
    not_null: false
    properties: {}
  - name: total
    type: DECIMAL
    is_calculated: false
    not_null: false
    properties: {}
primary_key: order_id
cached: false
properties: {}

relationships.yml

relationships:
  - name: orders_customer
    models:
      - orders
      - customers
    join_type: MANY_TO_ONE
    condition: orders.customer_id = customers.customer_id

views.yml

views: []

Load YAML project → MDL JSON

To assemble a YAML project back into an MDL JSON dict:

1. Read wren_project.yml → extract catalog, schema, data_source
2. Read every file in models/*.yml → collect into models list
3. Read relationships.yml → extract relationships list
4. Read views.yml → extract views list
5. Rename snake_case keys to camelCase (see Field mapping section below)
6. Assemble:

{
  "catalog": "<from wren_project.yml>",
  "schema": "<from wren_project.yml>",
  "dataSource": "<from wren_project.yml data_source>",
  "models": [...],
  "relationships": [...],
  "views": []
}

Build YAML project → target/

Same as Load above, but write the compiled file:

• <project_dir>/target/mdl.json — assembled MDL JSON (camelCase)

After building:

• Pass mdl_file_path="<project_dir>/target/mdl.json" to deploy() to activate the MDL
• Connection info is managed via the MCP server Web UI — no file needed

Field mapping

When converting between YAML (snake_case) and JSON (camelCase):

MDL fields:

All other MDL fields (name, type, catalog, schema, table, condition, models, columns, cached, properties) are the same in both formats.

Typical workflow

1. Generate MDL
   Follow the wren-generate-mdl skill to introspect the database and build the MDL JSON dict.

2. Save project
   Write wren_project.yml + models/*.yml + relationships.yml + views.yml
   (convert camelCase → snake_case from the MDL JSON).

3. Add target/ to .gitignore
4. Commit project directory to version control

5. Later — Build: read wren_project.yml, then models/*.yml, relationships.yml, views.yml.
                   Rename snake_case → camelCase, write target/mdl.json.

6. Connection info: configure via the MCP server Web UI
                   (typically http://localhost:9001; use the Docker host hint when running in a container)

7. Deploy: deploy(mdl_file_path="./target/mdl.json")