by pgplex
Minimal Postgres editor for speed, collaboration, and AI
# Add to your Claude Code skills
git clone https://github.com/pgplex/pgconsoleLast scanned: 6/26/2026
{
"issues": [],
"status": "PASSED",
"scannedAt": "2026-06-26T07:53:18.663Z",
"npmAuditRan": false,
"pipAuditRan": true,
"promptInjectionRan": true
}pgconsole is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by pgplex. Minimal Postgres editor for speed, collaboration, and AI. It has 113 GitHub stars.
Yes. pgconsole passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/pgplex/pgconsole" and add it to your Claude Code skills directory (see the Installation section above).
pgconsole is primarily written in TypeScript. It is open-source under pgplex on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh pgconsole against similar tools.
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[!NOTE] pgplex: Modern Developer Stack for Postgres - pgconsole · pgtui · pgschema · pgparser
Brought to you by Bytebase, open-source database DevSecOps 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.
Visit https://docs.pgconsole.com/getting-started/quickstart
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.
SELECT, WITH, and other blocksGenerate, explain, fix, and rewrite SQL with an AI assistant that understands your schema context. Supports OpenAI, Anthropic, and Google providers.
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.
/mcp; each agent authenticates with Authorization: Bearer <token>agent:<id> IAM rules) or a delegated agent that acts on behalf of a user, optionally capped to fewer permissions or connectionslist_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)# 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.
read, write, ddl, admin, explain, execute, export are independentEvery 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-..."
[!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
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