WrenAI
GenBI for AI agents, turns natural-language questions into trusted dashboards and SQL
GraphCanon updated 2d · GitHub synced 2d
Decision brief
WrenAI transforms natural-language queries into SQL and produces visual reports from over twenty supported data sources using an open context layer.
Good fit when
- When you require a tool that can generate trusted dashboards, charts, and SQL queries directly from natural language inputs.
- If your project involves integrating with multiple databases such as BigQuery, Snowflake, PostgreSQL, ClickHouse, Amazon Redshift, Databricks, and others, thereby benefiting from a versatile data-to-視
Avoid when
- For environments where the specific installation instructions for regions like mainland China might be problematic or where direct dependency on certain mirrors could cause operational challenges.
- When a project strictly requires proprietary tools or has licensing constraints that do not align with the Apache 2.0 license of WrenAI.
- Pricing:
- freemium - Free to use with self-hosting capabilities; commercial support available.
- Requirements:
- Install the CLI using pip (e.g., `pip install wrenai`). Consider regional mirrors like Tsinghua for faster installation in mainland China.
Observed Jul 11, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Very active (0d since push)
- As of 2d
- Provenance
- Not a fork · Organization account
- As of 2d
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install WrenAIHow it fits your stack(6)
Typed graph edges - alternatives, integrations, successors, and dependencies. Ranked by relationship type, not raw GitHub stars.
Related
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Optional deeper exploration of typed edges and category neighbours.
Similar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Open-source tool that translates natural language inputs into SQL queries and generates visualizations (charts and dashboards) from over twenty supported data sources.
Capability facts
- Languages
- python
Source: github.language · Aug 18, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 18, 2026)
npx skills add Canner/WrenAI # auto-detects Claude Code, Cursor, Cline,Source link
Source: README excerpt (regex_v1, Aug 18, 2026)
pip install wrenai # core (DuckDB included)Source link
Source: README excerpt (regex_v1, Aug 18, 2026)
npx skills add Canner/WrenAI # auto-detects Claude Code, Cursor, Cline, Codex, …Source link
Tags
README
1. Install the CLI
pip install wrenai # core (DuckDB included)
pip install "wrenai[postgres,memory]" # add per-datasource and memory extras as needed
Tip for users in mainland China: If
pip installis slow or fails, use the Tsinghua mirror:pip install wrenai -i https://pypi.tuna.tsinghua.edu.cn/simpleIf HuggingFace model downloads time out, add
export HF_ENDPOINT=https://hf-mirror.combefore running the CLI.
2. Install the discovery stub for your AI client
npx skills add Canner/WrenAI # auto-detects Claude Code, Cursor, Cline, Codex, …
The stub is ~50 lines. It teaches your agent to fetch workflow guides via
wren skills get <name> and shaped prompts via
wren ask "<question>" --guided|--direct, and everything else lives in the CLI.
License
Apache 2.0. See LICENSE.
Come build open GenBI with us.
If WrenAI helps you, drop a ⭐, it genuinely helps us grow!
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For agents
This page has a .md twin and JSON over the API.