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wren — Claude Code skill: what it does, how to install

Connects AI agents to the Wren semantic SQL layer across 22+ databases and SaaS sources. Solves data questions, generates MDL models, and scaffolds GenBI web apps.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓ 
npx skills add Canner/WrenAI --skill wren -a claude-code
Open on GitHub

What wren does

This skill acts as a discovery stub for the wren CLI, exposing a semantic SQL modeling layer over 22+ databases, including Postgres, MySQL, BigQuery, Snowflake, and Spark. The actual guides and workflows live directly inside the CLI tool rather than in static prompt files. This setup prevents prompt cache drift across software versions.

The agent gets execution access to Bash(wren:*). It loads step-by-step guides on demand via wren skills get <name>, inspects connection schemas, and tests transpiled queries with wren dry-plan without touching production databases. It also covers SaaS ingestion via dlt for tools like Stripe or HubSpot, and can scaffold GenBI dashboards for Vercel or Cloudflare.

The skill will fail unless you have the core CLI installed in your Python environment; run pip install wrenai before using it. If you need semantic memory commands like wren memory index or recall, install the package with the optional [memory] extra.

What it helps with

  • Translate business questions into valid SQL queries across data sources
  • Generate MDL modeling projects directly from database schemas
  • Ingest SaaS metrics from Stripe or Salesforce using dlt connectors
  • Deploy shareable GenBI analytics dashboards to Cloudflare or Vercel

Example prompts for the agent

  • Generate an MDL project from our Postgres schema using wren
  • Show me customer churn and revenue breakdown for this quarter via wren
  • Connect Stripe data using the wren dlt connector

How to install wren

1Skills CLI (Vercel)

npx skills add Canner/WrenAI --skill wren -a claude-code

2Manually: put the files in place

~/.claude/skills/wren/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/wren/

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Questions about wren

How to install wren in Claude Code?

Run npx skills add Canner/WrenAI --skill wren -a claude-code. You also need to install the core CLI package via pip install wrenai.

What does the wren skill do?

It gives the agent access to the Wren semantic data layer across 22+ databases. The agent can build data models, verify SQL queries, and deploy web analytics apps.

What is required for wren memory commands?

Commands like wren memory index, recall, and store require installing the Python package with the [memory] extra.

Source text

SKILL.md · Apache-2.0 
---
name: wren
description: "Wren CLI for AI agents — a semantic SQL layer over 22+ databases (Postgres, MySQL, BigQuery, Snowflake, Spark, …). The actual workflow guides live inside the `wren` CLI itself; this is just a discovery stub. Use whenever the user asks a data question (how many, show me, top N, compare, trend, breakdown, metric, revenue, customers, orders), wants to install / set up Wren Engine, connect a new database, connect SaaS data via dlt (HubSpot, Stripe, Salesforce, GitHub, Slack), generate or regenerate an MDL project from a database schema, enrich a project with business context (enum meanings, units, cubes like ARR / DAU / churn), or turn a project's context layer into a shareable GenBI web app / dashboard and deploy it to Vercel or Cloudflare. Triggers: 'install wren', 'set up wren engine', 'connect database to wren', 'connect SaaS to wren', 'load hubspot / stripe / salesforce data', 'generate mdl', 'scaffold wren project', 'enrich wren context', 'augment my project', 'add cubes', 'build a dashboard', 'make a shareable analytics app', 'deploy my context layer as a web app', 'genbi app', 'wren onboarding', 'wren usage', 'wren generate mdl', 'wren dlt connector', 'wren enrich context', 'wren genbi'."
license: Apache-2.0
allowed-tools: Bash(wren:*)
---

# Wren CLI

This is a discovery stub. The actual workflow guides and prompt helpers
live inside the `wren` CLI itself, so they always match the installed
wrenai version (no skill cache, no version drift).

Install: `pip install wrenai`.

## Workflow guides

```bash
wren skills list                        # all available workflow guides
wren skills get onboarding              # set up Wren end-to-end
wren skills get usage                   # day-to-day querying
wren skills get generate-mdl            # generate MDL from a database schema
wren skills get dlt-connector           # connect SaaS sources via dlt
wren skills get enrich-context          # add business context (units, enums, cubes)
wren skills get genbi                   # build & deploy a shareable GenBI web app
# add --full to include the skill's reference docs
# add --script <name> to fetch a bundled script (e.g. dlt-connector / introspect_dlt)
```

## Reference docs

Full reference docs live on the web: <https://github.com/Canner/WrenAI/tree/main/docs/core>

```bash
wren docs connection-info <ds>          # required + optional connection fields for a data source
```

## Prompt enhancement (wraps a user question for an agent)

```bash
wren ask "<question>" --guided          # for weaker LLMs (strict task flow)
wren ask "<question>" --direct          # for stronger LLMs (minimal wrapping)
```

## Day-to-day data commands (not a sub-app — top-level)

```bash
wren --sql '...'                        # execute SQL through the MDL layer
wren query --sql '...'                  # same, explicit
wren dry-plan --sql '...'               # transpile only, no DB hit
wren context show / build / validate    # project / MDL lifecycle
wren profile add / list / switch        # named connection profiles
wren memory index / recall / store      # semantic memory (needs `[memory]` extra)
```

Run `wren --help` for the full surface; load the matching `wren skills get
<name>` guide before driving any multi-step workflow.

© Canner · Apache-2.0 · Canner/WrenAI

See also

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