postgres-mcp

postgres-mcp

MCP server with 14 tools for PostgreSQL database operations. Query databases, explore schemas, analyze tables, with SQL injection prevention and read-only mode by default.

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PostgreSQL MCP Server

<!-- mcp-name: io.github.JaviMaligno/postgresql -->

CI PyPI version Python 3.10+ License: MIT

MCP server for PostgreSQL database operations. Works with Claude Code, Claude Desktop, and any MCP-compatible client.

Features

  • Query Execution: Execute SQL queries with read-only protection by default
  • Schema Exploration: List schemas, tables, views, and functions
  • Table Analysis: Describe structure, indexes, constraints, and statistics
  • Performance Tools: EXPLAIN queries and analyze table health
  • Security First: SQL injection prevention, credential protection, read-only by default
  • MCP Prompts: Guided workflows for exploration, query building, and documentation
  • MCP Resources: Browsable database structure as markdown

Quick Start

# Install
pipx install postgresql-mcp

# Configure Claude Code
claude mcp add postgres -s user \
  -e POSTGRES_HOST=localhost \
  -e POSTGRES_USER=your_user \
  -e POSTGRES_PASSWORD=your_password \
  -e POSTGRES_DB=your_database \
  -- postgresql-mcp

Full Installation Guide - Includes database permissions setup, remote connections, and troubleshooting.

Available Tools (14 total)

Query Execution

Tool Description
query Execute read-only SQL queries against the database
execute Execute write operations (INSERT/UPDATE/DELETE) when enabled
explain_query Get EXPLAIN plan for query optimization

Schema Exploration

Tool Description
list_schemas List all schemas in the database
list_tables List tables in a specific schema
describe_table Get table structure (columns, types, constraints)
list_views List views in a schema
describe_view Get view definition and columns
list_functions List functions and procedures

Performance & Analysis

Tool Description
table_stats Get table statistics (row count, size, bloat)
list_indexes List indexes for a table
list_constraints List constraints (PK, FK, UNIQUE, CHECK)

Database Info

Tool Description
get_database_info Get database version and connection info
search_columns Search for columns by name across all tables

MCP Prompts

Guided workflows that help Claude assist you effectively:

Prompt Description
explore_database Comprehensive database exploration and overview
query_builder Help building efficient queries for a table
performance_analysis Analyze table performance and suggest optimizations
data_dictionary Generate documentation for a schema

MCP Resources

Browsable database structure:

Resource URI Description
postgres://schemas List all schemas
postgres://schemas/{schema}/tables Tables in a schema
postgres://schemas/{schema}/tables/{table} Table details
postgres://database Database connection info

Example Usage

Once configured, ask Claude to:

Schema Exploration:

  • "List all tables in the public schema"
  • "Describe the users table structure"
  • "What views are available?"

Querying:

  • "Show me 10 rows from the orders table"
  • "Find all customers who placed orders last week"
  • "Count records grouped by status"

Performance Analysis:

  • "What indexes exist on the orders table?"
  • "Analyze the performance of the users table"
  • "Explain this query: SELECT * FROM orders WHERE created_at > '2024-01-01'"

Documentation:

  • "Generate a data dictionary for this database"
  • "What columns contain 'email' in their name?"

Security

This MCP server implements multiple security layers:

Read-Only by Default

Write operations (INSERT, UPDATE, DELETE) are blocked unless explicitly enabled via ALLOW_WRITE_OPERATIONS=true.

SQL Injection Prevention

  • All queries are validated before execution
  • Dangerous operations (DROP DATABASE, etc.) are always blocked
  • Multiple statements are not allowed
  • SQL comments are blocked

Credential Protection

  • Passwords stored using Pydantic's SecretStr
  • Credentials never appear in logs or error messages

Query Limits

  • Results limited by MAX_ROWS (default: 1000)
  • Query timeout configurable via QUERY_TIMEOUT

Installation Options

From PyPI (Recommended)

pipx install postgresql-mcp
# or
pip install postgresql-mcp

From Source

git clone https://github.com/JaviMaligno/postgres_mcp.git
cd postgres_mcp
uv sync

Configuration

Claude Code CLI (Recommended)

claude mcp add postgres -s user \
  -e POSTGRES_HOST=localhost \
  -e POSTGRES_PORT=5432 \
  -e POSTGRES_USER=your_user \
  -e POSTGRES_PASSWORD=your_password \
  -e POSTGRES_DB=your_database \
  -- postgresql-mcp

Cursor IDE

Add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "postgres": {
      "command": "postgresql-mcp",
      "env": {
        "POSTGRES_HOST": "localhost",
        "POSTGRES_PORT": "5432",
        "POSTGRES_USER": "your_user",
        "POSTGRES_PASSWORD": "your_password",
        "POSTGRES_DB": "your_database"
      }
    }
  }
}

Environment Variables

Variable Required Default Description
POSTGRES_HOST Yes localhost Database host
POSTGRES_PORT No 5432 Database port
POSTGRES_USER Yes postgres Database user
POSTGRES_PASSWORD Yes - Database password
POSTGRES_DB Yes postgres Database name
POSTGRES_SSLMODE No prefer SSL mode
ALLOW_WRITE_OPERATIONS No false Enable write operations
QUERY_TIMEOUT No 30 Query timeout (seconds)
MAX_ROWS No 1000 Maximum rows returned

Development

Requirements

  • Python 3.10+
  • uv for dependency management
  • PostgreSQL for integration tests

Setup

git clone https://github.com/JaviMaligno/postgres_mcp.git
cd postgres_mcp
uv sync

Running Tests

# Unit tests (no database required)
uv run pytest tests/test_security.py tests/test_settings.py tests/test_models.py tests/test_utils.py -v

# Integration tests (requires PostgreSQL)
docker-compose up -d
export POSTGRES_HOST=localhost POSTGRES_PORT=5433 POSTGRES_USER=testuser POSTGRES_PASSWORD=testpass POSTGRES_DB=testdb
uv run pytest tests/test_integration.py -v

# All tests
docker-compose up -d && uv run pytest -v

# All tests (requires PostgreSQL)
uv run pytest -v --cov=postgres_mcp

CI/CD Pipeline

The project uses GitHub Actions:

  • Every push to main: Runs tests on Python 3.10, 3.11, 3.12
  • Pull requests: Full test suite
  • Tags (v*): Tests, builds, and publishes to PyPI

To release a new version:

# 1. Update version in postgres_mcp/__version__.py
# 2. Commit and push
git add -A && git commit -m "release: v0.2.0"
git push origin main

# 3. Create and push tag (triggers PyPI publish)
git tag v0.2.0
git push origin v0.2.0

Troubleshooting

Connection Issues

# Verify PostgreSQL is running
pg_isready -h localhost -p 5432

# Test connection with psql
psql -h localhost -U your_user -d your_database

Permission Denied

Ensure your database user has SELECT permissions:

GRANT SELECT ON ALL TABLES IN SCHEMA public TO your_user;

MCP Server Not Connecting

# Check server status
claude mcp get postgres

# Test server directly
postgresql-mcp  # Should wait for MCP messages

Links

License

MIT

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