A CLI tool that converts database schemas into the Toon schema definition format.
git clone https://github.com/kamil5b/db2toon{
"mcpServers": {
"db2toon": {
"command": "db2toon"
}
}
}MCP Servers overview
# db2toon
A CLI tool that converts database schemas into the Toon schema definition format.
## Overview
`db2toon` connects to a database and extracts schema information (tables, columns, types, constraints, indexes, and examples), then converts it into the human-readable Toon format for database design documentation and visualization. PostgreSQL, SQLite, DuckDB, MySQL/MariaDB, and CockroachDB are supported. `pg2toon` remains a PostgreSQL compatibility command.
## Features
- **Schema Extraction**: Automatically extracts tables, columns, and metadata from PostgreSQL, SQLite, DuckDB, MySQL/MariaDB, and CockroachDB
- **Type Normalization**: Simplifies PostgreSQL types (e.g., `character varying` → `varchar`)
- **Relationship Mapping**: Converts foreign key constraints to inline references or multi-column references
- **Comment Preservation**: Includes comments where the database exposes them; SQLite does not have catalog comments
- **Index Documentation**: Extracts and documents database indexes
- **Cross-Platform**: Builds without CGO for Linux, macOS, and Windows (amd64 and arm64)
## Installation
### From Source
```bash
git clone https://github.com/kamil5b/db2toon.git
cd db2toon
CGO_ENABLED=0 go build -o output/db2toon ./cmd/db2toon
CGO_ENABLED=0 go build -o output/pg2toon ./cmd/pg2toon
```
### From Releases
Download pre-built binaries from the [releases page](https://github.com/kamil5b/db2toon/releases) for your platform.
## Usage
### LLM tool integration
Build and run the MCP-compatible stdio server:
```bash
CGO_ENABLED=0 go build -o output/db2toon-mcp ./cmd/db2toon-mcp
./output/db2toon-mcp
```
The server exposes `db2toon.extract_schema`. Its required arguments are
`dialect` (`postgres`, `sqlite`, `duckdb`, `mysql`, `mariadb`, or `cockroachdb`) and `db`; optional extraction settings are supplied in
an `options` object. The tool is read-only, uses a 30-second default timeout,
and limits responses to 4 MiB. Set `options.timeout` and
`options.max_output_bytes` to lower limits when needed. Connection strings are
never included in tool errors or results.
### Basic Usage
```bash
./db2toon postgres -db "postgresql://user:password@localhost/dbname"
# SQLite database file
./db2toon sqlite -db ./schema.db
# DuckDB database file (requires libduckdb at runtime)
./db2toon duckdb -db ./analytics.duckdb
# Compatibility command; PostgreSQL is selected automatically.
./pg2toon -db "postgresql://user:password@localhost/dbname"
```
### Save to File
```bash
./db2toon postgres -db "postgresql://user:password@localhost/dbname" -out schema.toon
```
Include up to two sample rows per PostgreSQL table in the TOON output, using a
stable ordering and a reproducible sample seed:
```bash
./db2toon postgres -db "postgresql://user:password@localhost/dbname" \
-example-sample=2 -example-sample-ordered=true -seed=42
```
The default `-example-sample=0` omits `@example` sections.
SQLite and DuckDB also support `-example-sample`, but currently use a simple
`LIMIT` query. `-example-sample-ordered` and `-seed` are currently effective
only for PostgreSQL.
Select multiple schemas, include partitioned tables, and change the default
30-second operation timeout with:
```bash
./db2toon postgres -db "$DATABASE_URL" -schema audit
./db2toon postgres -db "$DATABASE_URL" -schemas public,audit -include-partitioned -timeout 1m
# SQLite and DuckDB default to the `main` schema.
./db2toon sqlite -db ./schema.db -schema main
./db2toon duckdb -db ./analytics.duckdb -schema analytics
```
### Flags
- `-db string`: Database connection URL or local database path (required)
- `dialect`: `postgres`, `sqlite`, `duckdb`, `mysql`, `mariadb`, or `cockroachdb` for `db2toon`; `pg2toon` always uses PostgreSQL
- `-out string`: Output file path (optional, defaults to stdout)
- `-schema string`: A single schema to extract (defaults to `public` for PostgreSQL and `main` for SQLite/DuckDB)
- `-schemas string`: Comma-separated schemas to extract; cannot be combined with `-schema`
- `-include-partitioned`: Include PostgreSQL partitioned tables
- `-exclude-tables string`: Comma-separated tables to exclude entirely; accepts `table` or `schema.table`
- `-exclude-example-tables string`: Comma-separated tables to exclude from `@example` sampling
- `-exclude-example-fields string`: Comma-separated qualified fields to exclude from examples, such as `public.users.password_hash`
- `-example-sample int`: Number of sample rows to include per table (defaults to `0`)
- `-example-sample-ordered`: Select sample rows using deterministic ordering for PostgreSQL (defaults to `false`)
- `-seed int`: Seed for reproducible PostgreSQL sample selection (defaults to `0`; currently ignored by SQLite/DuckDB)
- `-timeout duration`: Connection and extraction timeout (defaults to `30s`)
## Output Format
The Toon format provides a clean, human-readable schema definition:
```
[users]
# User accounts table
id int {pk}
email varchar {req}
name varchar
created_at timestamptz {req}
@indices
idx_email: ON users USING btree (email)
@example[2]{id,email,name,created_at}:
1,alice@example.com,Alice,2026-01-10T09:00:00Z
2,bob@example.com,Bob,2026-01-11T10:30:00Z
[posts]
# Blog posts
id int {pk}
user_id int {req} -> users(id)
title varchar {req}
content text
published_at timestamptz
[comments]
# Post comments
id int {pk}
post_id int {req} -> posts(id)
user_id int {req} -> users(id)
content text {req}
created_at timestamptz {req}
```
### Format Elements
- `[TableName]`: Table definition
- `# comment`: Table or column comments
- `name type {tags}`: Column definition with optional tags
- `{pk}`: Primary key
- `{req}`: Required (NOT NULL)
- Multiple tags: `{pk,req}`
- `-> table(column)`: Foreign key reference (inline for single columns)
- `@indices`: Section for database indexes
- `@example[n]{columns}:`: Up to `n` sampled rows from the table
- `// comment`: Inline column comment
## Requirements
- Go 1.26.0 or later
- PostgreSQL 9.4+ (for JSON aggregation functions), SQLite, DuckDB, MySQL/MariaDB, or CockroachDB
- A valid database connection string or local database path
- DuckDB also requires a compatible `libduckdb` shared library at runtime
## License
MIT
What people ask about db2toon
What is kamil5b/db2toon?
+
kamil5b/db2toon is mcp servers for the Claude AI ecosystem. A CLI tool that converts database schemas into the Toon schema definition format. It has 2 GitHub stars and was last updated today.
How do I install db2toon?
+
You can install db2toon by cloning the repository (https://github.com/kamil5b/db2toon) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
Is kamil5b/db2toon safe to use?
+
kamil5b/db2toon has not been audited yet by our security agent. Review the original repository on GitHub before using it in production.
Who maintains kamil5b/db2toon?
+
kamil5b/db2toon is maintained by kamil5b. The last recorded GitHub activity is from today, with 0 open issues.
Are there alternatives to db2toon?
+
Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.
Deploy db2toon to your cloud
Ship this repo to production in minutes. Each platform spins up its own environment with editable env vars.
Maintain this repo? Add a badge to your README
Drop the badge into your GitHub README to show it's tracked on ClaudeWave. Each badge links back to this page and reflects the live Trust Score.
[](https://claudewave.com/repo/kamil5b-db2toon)<a href="https://claudewave.com/repo/kamil5b-db2toon"><img src="https://claudewave.com/api/badge/kamil5b-db2toon" alt="Featured on ClaudeWave: kamil5b/db2toon" width="320" height="64" /></a>More MCP Servers
Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
An open-source AI agent that brings the power of Gemini directly into your terminal.
The fastest path to AI-powered full stack observability, even for lean teams.
Real-time global intelligence dashboard. AI-powered news aggregation, geopolitical monitoring, and infrastructure tracking in a unified situational awareness interface
🕷️ An adaptive Web Scraping framework that handles everything from a single request to a full-scale crawl!