database-scout

# database-scout Read-only exploration tool for SQLite / PostgreSQL databases — inspect table schemas, preview data, generate ER diagrams, and run safe queries. ## Feature Overview | Feature | Description | |---------|-------------| | List all tables | Show tables and views in the database, with row counts | | Inspect table schema | Column names, types, constraints (PK/FK/NOT NULL), indexes, defaults | | Data preview | View the first N rows of a table | | ER diagram generation | Output Mermaid erDiagram syntax, ready to render | | Safe read-only queries | Only SELECT/WITH/EXPLAIN allowed; write operations are blocked | ## Security Mechanisms - **Connection-level read-only**: SQLite opens with `?mode=ro` URI; PostgreSQL uses `SET SESSION READ ONLY` - **SQL whitelist**: Only statements starting with SELECT / WITH / EXPLAIN / PRAGMA / SHOW are allowed - **Dangerous keyword blocking**: INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, and 30+ other keywords are blocked - **Multi-statement blocking**: Semicolon-separated multiple SQL statements are rejected (prevents injection) - **Identifier escaping**: Table names are double-quote escaped to prevent SQL injection ## Quick Start ```bash # List all tables in a SQLite database python3 scripts/db_explorer.py --db-path data.db list-tables # Inspect table schema python3 scripts/db_explorer.py --db-path data.db describe users # Preview data (default 20 rows) python3 scripts/db_explorer.py --db-path data.db preview orders --limit 10 # Generate Mermaid ER diagram python3 scripts/db_explorer.py --db-path data.db er-diagram # Run a read-only query python3 scripts/db_explorer.py --db-path data.db query "SELECT name, age FROM users WHERE age > 18 LIMIT 10" ``` ### PostgreSQL ```bash # Connect to PostgreSQL python3 scripts/db_explorer.py --db-type postgres --dsn "host=localhost dbname=mydb user=reader" list-tables # Inspect table schema python3 scripts/db_explorer.py --db-type postgres --dsn "host=localhost dbname=mydb user=reader" describe orders ``` ## Detailed Usage ### Parameters | Parameter | Required | Default | Description | |-----------|----------|---------|-------------| | `--db-type` | No | sqlite | Database type: sqlite or postgres | | `--db-path` | Yes (for SQLite) | — | Path to the SQLite database file | | `--dsn` | Yes (for PostgreSQL) | — | PostgreSQL connection string | ### Subcommands | Command | Description | Example | |---------|-------------|---------| | `list-tables` | List all tables/views | `list-tables` | | `describe <table>` | Show detailed table schema | `describe users` | | `preview <table> [--limit N / -n N]` | Preview the first N rows | `preview orders --limit 5` | | `er-diagram` | Generate Mermaid ER diagram | `er-diagram` | | `query "<sql>"` | Run a read-only SQL query | `query "SELECT count(*) FROM users"` | ## Output Examples ### list-tables ```json [ {"name": "users", "type": "table", "row_count": 1500}, {"name": "orders", "type": "table", "row_count": 8200}, {"name": "user_stats", "type": "view", "row_count": 1500} ] ``` ### describe ```json { "table": "orders", "row_count": 8200, "columns": [ {"cid": 0, "name": "id", "type": "INTEGER", "notnull": true, "default": null, "primary_key": true}, {"cid": 1, "name": "user_id", "type": "INTEGER", "notnull": true, "default": null, "primary_key": false}, {"cid": 2, "name": "amount", "type": "REAL", "notnull": false, "default": "0.0", "primary_key": false} ], "foreign_keys": [ {"from": "user_id", "to_table": "users", "to_column": "id"} ], "indexes": [ {"name": "idx_orders_user_id", "unique": false, "columns": ["user_id"]} ] } ``` ### er-diagram (Mermaid) ```mermaid erDiagram users { INTEGER id PK TEXT name TEXT email INTEGER age } orders { INTEGER id PK INTEGER user_id FK REAL amount TEXT created_at } users ||--o{ orders : "user_id" ``` ## Dependencies - Python 3.8+ (`sqlite3` is a built-in module) - PostgreSQL support requires: `pip install psycopg2-binary` ## Activation Triggers Triggered by requests to explore a database, view table structures, describe tables, generate diagrams, or query data, and by keywords like database exploration, schema, ER diagram, or SQL query.