Wren CLI
SkillDatabases & dataLets your agent answer data questions by running SQL across Postgres, BigQuery, Snowflake and other databases.
Available today. Use it from your connected AI after setup.
No other account needed.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Wren CLI skill
About this skill
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, breakd
What this skill tells your AI
The instructions your AI receives, as published by canner/wrenai in skills/wren/SKILL.md and read by ahel’s review.
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
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
wren docs connection-info <ds> # required + optional connection fields for a data source
Prompt enhancement (wraps a user question for an agent)
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)
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.
Signals
- GitHub stars
- 18k
- Forks
- 2k
- Last commit
- Sep 2026
ahel review
K1binfo
installs-packages
Automated review, not a security audit. Ruleset v1+k2.
Advanced
- Item type
- skill
- Key
wrenai-wren- Source
- github.com/canner/wrenai