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postgresql-mcp

postgresql-mcp

by udaykumar-dhokia
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

PostgreSQL MCP

A Model Context Protocol (MCP) server that provides AI assistants (like Claude) with tools to directly interact with PostgreSQL databases securely.

Features

  • create_table: Create a new table with custom columns.

  • list_tables: List all tables in the public schema.

  • describe_table: Get the schema and column details of a specific table.

  • execute_sql: Execute arbitrary SQL queries.

  • Web Configurator: A built-in local web UI to securely manage connection strings and generate API keys.

Related MCP server: PostgreSQL API SSH MCP Server

Installation

You can install and run this package easily using uv:

# Run without installing globally
uvx postgresql-mcp

# Or install globally for easy access
uv tool install postgresql-mcp

Setup & Configuration

This project requires an API Key mapped to your PostgreSQL database URL. To easily set this up, we provide a built-in Web Configurator.

1. Generate an API Key

Run the web configurator:

postgresql-mcp-web

Or, if running without global installation:

uvx --from . postgresql-mcp-web

Open your browser to http://localhost:8000. Enter your database URL (postgresql://user:pass@host/db) and click "Generate API Key".

The application securely stores your credentials in ~/.sql-mcp/keys.json and outputs a configuration snippet.

2. Connect Claude Desktop

Copy the generated snippet and add it to your Claude Desktop configuration file (typically located at %APPDATA%\Claude\claude_desktop_config.json on Windows or ~/Library/Application Support/Claude/claude_desktop_config.json on macOS).

{
  "mcpServers": {
    "postgresql-mcp": {
      "command": "uvx",
      "args": [
        "postgresql-mcp"
      ],
      "env": {
        "API_KEY": "postgresql-mcp-your-generated-key"
      }
    }
  }
}

Restart Claude Desktop, and your AI assistant will now be able to interact with your database!

Usage Tracking

The server automatically tracks how many times each API key is utilized. You can view this data locally in ~/.sql-mcp/usage.json.

Contributing

We welcome contributions! Please see CONTRIBUTING.md for details on how to get started.

Available Tools

4 tools
create_tableA

Create a table with custom columns.

Example: table_name = "users" columns = { "id": "SERIAL PRIMARY KEY", "name": "TEXT NOT NULL", "age": "INT", "created_at": "TIMESTAMP DEFAULT CURRENT_TIMESTAMP" }

Inputs: columns (required), table_name (required). Returns: result

describe_tableA

Describe table structure (columns, types, nullability, default).

Inputs: table_name (required). Returns: result

execute_sqlB

Execute any SQL query. WARNING: Full database access.

Inputs: query (required).

list_tablesA

List all tables in the public schema.

Inputs: no named parameters. Returns: result

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    Deploy Server
    Claude Code, inside the Godot 4 editorFlockbay puts an AI agent in the real Godot 4 editor: it writes GDScript, runs your game and fixes what breaks. Free, or bring your own Claude Code or Codex.flockbay.comAd

    TDQS

    A3.7/5.0

    Scored across 4 tools

    Disambiguation4/5

    The structured tools (create_table, list_tables, describe_table) have clear, distinct purposes, and execute_sql is explicitly a general SQL escape hatch. However, execute_sql overlaps with all of them, especially create_table, since table creation can be done through either tool.

    Naming Consistency5/5

    All tool names follow the same verb_noun snake_case pattern: create_table, list_tables, describe_table, execute_sql. There are no mixed conventions or inconsistent verb styles.

    Tool Count5/5

    Four tools is a reasonable, well-scoped set for a PostgreSQL server: three schema-oriented helpers plus one arbitrary SQL tool. Each tool has a clear role and none feel redundant or missing.

    Completeness4/5

    The set covers schema creation, listing, and inspection, and execute_sql provides full database access as a fallback. Row-level CRUD and operations like ALTER/DROP are not exposed as first-class tools, but they can be handled through execute_sql, leaving only minor gaps.

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