ReddRadar
Agent skill
wren-connection-info
Reference guide for Wren Engine connection info — explains required fields for all 18 supported data sources (PostgreSQL, MySQL, BigQuery, Snowflake, ClickHouse, Trino, DuckDB, Databricks, Spark, Athena, Redshift, Oracle, SQL Server, Apache Doris, S3, GCS, MinIO, local files). Covers sensitive field handling, Docker host hints, and BigQuery credential encoding. Use when the user asks how to configure a data source connection or what fields to fill in.
Install this agent skill to your Project
npx add-skill https://github.com/Canner/wren-engine/tree/main/skills-archive/wren-connection-info
Metadata
Additional technical details for this skill
- author
- wren-engine
- version
- 1.5
SKILL.md
Wren Connection Info Reference
Connection info can only be configured through the MCP server Web UI at http://localhost:9001. Do not attempt to set it programmatically. Always direct the user to the Web UI.
Supported data sources
| Value | Database | Fields reference |
|---|---|---|
POSTGRES |
PostgreSQL | databases.md |
MYSQL |
MySQL / MariaDB | databases.md |
MSSQL |
SQL Server | databases.md |
CLICKHOUSE |
ClickHouse | databases.md |
ORACLE |
Oracle | databases.md |
DORIS |
Apache Doris | databases.md |
REDSHIFT |
Amazon Redshift | databases.md |
TRINO |
Trino | databases.md |
BIGQUERY |
Google BigQuery | databases.md |
SNOWFLAKE |
Snowflake | databases.md |
DUCKDB |
DuckDB | databases.md |
ATHENA |
AWS Athena | databases.md |
DATABRICKS |
Databricks | databases.md |
SPARK |
Apache Spark | databases.md |
S3_FILE |
Amazon S3 | file-sources.md |
GCS_FILE |
Google Cloud Storage | file-sources.md |
MINIO_FILE |
MinIO | file-sources.md |
LOCAL_FILE |
Local files | file-sources.md |
Read the linked reference file for the user's data source to get required fields, default ports, and setup notes.
Common patterns
Most database connectors need: host, port, user, password, database.
Exceptions:
- BigQuery — uses
project_id,dataset_id,credentials(base64-encoded). See databases.md for encoding instructions. - Snowflake — uses
accountinstead ofhost, plusschema. - Trino — needs
catalogandschemainstead ofdatabase. - Databricks — uses
serverHostname,httpPath,accessToken(or service principal withclientId,clientSecret). - Spark — only
hostandport(Spark Connect protocol, no auth fields). - File sources — use
url,format, plus bucket/credentials. See file-sources.md.
Docker host hint
If the database runs on the host machine and Wren Engine runs inside Docker, localhost cannot reach the host. Use host.docker.internal instead:
| Original | Inside Docker |
|---|---|
localhost |
host.docker.internal |
127.0.0.1 |
host.docker.internal |
| Cloud/remote hostname | No change needed |
Sensitive fields
Never log, display, or pass sensitive values through the AI agent unnecessarily.
| Connector | Sensitive fields |
|---|---|
| Postgres / MySQL / MSSQL / ClickHouse / Oracle / Doris / Redshift | password |
| BigQuery | credentials |
| Snowflake | password |
| Athena | aws_access_key_id, aws_secret_access_key |
| Databricks (token) | accessToken |
| Databricks (service principal) | clientId, clientSecret |
| S3 / MinIO | access_key, secret_key |
| GCS | key_id, secret_key, credentials |
| Trino / Spark / Local files | (none) |
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
Canner/wren-engine
wren-usage
Wren Engine CLI workflow guide for AI agents. Answer data questions end-to-end using the wren CLI: gather schema context, recall past queries, write SQL through the MDL semantic layer, execute, and learn from confirmed results. Use when: user asks a data question, requests a report or analysis, asks about metrics, revenue, customers, orders, trends, or any business data; user says 'how many', 'show me', 'what is the', 'top N', 'compare', 'trend', 'growth', 'breakdown'; user wants to explore, analyze, filter, aggregate, or summarize data from a database; agent needs to query data, connect a data source, handle errors, or manage MDL changes via the wren CLI.
Canner/wren-engine
wren-generate-mdl
Generate a Wren MDL project by exploring a database with available tools (SQLAlchemy, database drivers, MCP connectors, or raw SQL). Guides agents through schema discovery, type normalization, and MDL YAML generation using the wren CLI. Use when: user wants to create or set up a new MDL, onboard a new data source, or scaffold a project from an existing database.
Canner/wren-engine
wren-dlt-connector
Connect SaaS data (HubSpot, Stripe, Salesforce, GitHub, Slack, etc.) to Wren Engine for SQL analysis. Guides the user through the full flow: install dlt, pick a SaaS source, set up credentials, run the data pipeline into DuckDB, then auto-generate a Wren semantic project from the loaded data. Use this skill whenever the user mentions: connecting SaaS data, importing data from an API, dlt pipelines, loading HubSpot/Stripe/Salesforce/GitHub/Slack data, querying SaaS data with SQL, or setting up a new data source from a REST API. Also trigger when the user already has a dlt-produced DuckDB file and wants to create a Wren project from it.
Canner/wren-engine
wren-usage
Wren Engine — semantic SQL engine for AI agents. Query 22+ data sources (PostgreSQL, BigQuery, Snowflake, MySQL, ClickHouse, etc.) through a modeling layer (MDL). This skill is the main entry point: it guides setup, delegates to focused sub-skills for SQL authoring, MDL generation, project management, and MCP server operations. Use when: write SQL, query data, generate or update MDL, change database connection, manage YAML projects, set up or operate MCP server, or get started with Wren Engine for the first time.
Canner/wren-engine
wren-mcp-setup
Set up Wren Engine MCP server via Docker and register it with an AI agent. Covers pulling the Docker image, running the container with docker run, mounting a workspace, configuring connection info via the Web UI (with Docker host hint), registering the MCP server in Claude Code (or other MCP clients) using streamable-http transport, and starting a new session to interact with Wren MCP. Trigger when a user wants to run Wren MCP in Docker, configure Claude Code MCP, or connect an AI client to a Dockerized Wren Engine.
Canner/wren-engine
wren-project
Save, load, and build Wren MDL manifests as YAML project directories for version control. Use when a user wants to persist an MDL as human-readable YAML files, load a YAML project back into MDL JSON, or compile a YAML project to a deployable mdl.json file.
Didn't find tool you were looking for?