pgconsole

> [!NOTE]

> pgplex: The Postgres Toolchain for Humans and Agents - pgconsole · pgschema · pgtui · pgparser

>

> Brought to you by Bytebase, open-source database governance platform.

pgconsole is a web-based PostgreSQL editor. Single binary, single config file, no database required. Connect your team to PostgreSQL with access control and audit logging built in.

Installation

Visit https://docs.pgconsole.com/getting-started/quickstart

Prerequisites

• Node.js 20+

npm

npm install -g @pgplex/pgconsole
pgconsole --config pgconsole.toml

npx

npx @pgplex/pgconsole --config pgconsole.toml

Docker

docker run -p 9876:9876 -v /path/to/pgconsole.toml:/etc/pgconsole.toml pgplex/pgconsole

Run without `--config` to start in demo mode with a bundled sample database.

Features

SQL Editor

A full-featured SQL workspace for writing, running, editing, and inspecting PostgreSQL, with parser-powered intelligence in the editor.

• Autocomplete — context-aware suggestions for tables, columns, joins, and CTEs
• Formatting — pretty-print or collapse SQL to one line
• Error detection — red underlines with hover tooltips
• Code folding — collapse `SELECT`, `WITH`, and other blocks
• Function signature help — parameter hints as you type
• Result grid & inline editing — virtual-scrolling query results with staged edits, generated SQL previews, and optional AI risk assessment before execution
• Schema browser — inspect tables, views, materialized views, functions, and procedures with metadata, indexes, constraints, triggers, and grants

AI Assistant

Generate, explain, fix, and rewrite SQL with an AI assistant that understands your schema context. Supports OpenAI, Anthropic, and Google providers.

• Text-to-SQL — describe a query in natural language, get SQL back
• Explain SQL — get plain-language explanations of any query
• Fix SQL — AI-powered error correction from inline linting
• Rewrite SQL — optimize queries for performance or readability
• Risk assessment — analyze staged changes for potential risks before execution

MCP Server

Expose your Postgres connections to external AI agents (Claude, Cursor, IDEs, CI bots) over the Model Context Protocol — without handing out raw database credentials. Agents connect to a remote MCP endpoint and inherit the same IAM, permission, and audit controls as human users.

• Remote & token-authenticated — a Streamable HTTP endpoint at `/mcp`; each agent authenticates with `Authorization: Bearer `
• Two agent kinds — a *pure* service account (authorized by `agent:` IAM rules) or a *delegated* agent that acts on behalf of a user, optionally capped to fewer permissions or connections
• Permission-shaped tools — every agent can `list_connections`; catalog tools (`list_objects`, `describe_table`) appear once it has an accessible connection, and execution tools unlock per grant: `explain_query` (`explain`), `query` (`read`), `write_data` (`write`), `run_ddl` (`ddl`)
• Same governance as the UI — every statement runs through per-statement SQL permission detection, default-deny IAM, and the audit log

# A standalone agent, authorized via [[iam]] just like a user
[[agents]]
id = "ci-bot"
name = "CI Pipeline"
token = "generate-a-long-random-secret"   # openssl rand -hex 32

[[iam]]
connection = "staging"
permissions = ["read", "ddl"]
members = ["agent:ci-bot"]

Database Access Control

Fine-grained IAM controls who can read, write, or administer each connection. Permissions are enforced at the application layer — no database roles needed.

• Default deny — users have no access unless a rule explicitly grants it
• Connection-scoped — permissions are granted per connection, not globally
• Disjoint permissions — `read`, `write`, `ddl`, `admin`, `explain`, `execute`, `export` are independent

Audit Log

Every query and login is recorded as structured JSON to stdout. Filter and forward to your log infrastructure.

{
  "type": "audit",
  "ts": "2024-01-15T10:32:15.456Z",
  "action": "sql.execute",
  "actor": "alice@example.com",
  "connection": "prod-db",
  "sql": "SELECT * FROM users WHERE active = true",
  "duration_ms": 45,
  "row_count": 150
}

Single-File Configuration

Everything lives in `pgconsole.toml` — connections, users, groups, access rules, AI providers. No database required.

[[connections]]
id = "production"
name = "Production"
host = "db.example.com"
port = 5432
database = "myapp"
username = "readonly"
password = "..."

[[iam]]
connection = "production"
permissions = ["read", "explain", "export"]
members = ["*"]

[[iam]]
connection = "production"
permissions = ["*"]
members = ["group:dba"]

[[ai.providers]]
id = "claude"
vendor = "anthropic"
model = "claude-sonnet-4-20250514"
api_key = "sk-ant-..."

Getting Help

• Docs
• GitHub Issues

Development

> [!NOTE]

> For external contributors: If you want to request a feature, please create a GitHub issue to discuss first instead of creating a PR directly.

git clone https://github.com/pgplex/pgconsole.git
cd pgconsole
pnpm install
pnpm dev        # Start dev server (frontend + backend)
pnpm build      # Production build
pnpm test       # Run all tests

Sponsor

Bytebase - open source, web-based database DevSecOps platform.