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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.

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

• Node.js 20+

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

npx @pgplex/pgconsole --config pgconsole.toml

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.

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

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

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 <token>
• Two agent kinds — a pure service account (authorized by agent:<id> 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"]

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

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
}

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-..."

• Docs
• GitHub Issues

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

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