PostgreSQL MCP Server
Enables AI assistants to securely interact with PostgreSQL databases, offering 30+ tools, role-based access control, and security guardrails.
README
PostgreSQL MCP Server
A production-ready Model Context Protocol (MCP) server for PostgreSQL, enabling AI assistants to securely interact with PostgreSQL databases.
Features
- 30+ MCP tools for database operations
- Security guardrails with SQL injection detection
- Role-based access control (Viewer, Analyst, Developer, DBA, Admin)
- Read-only mode for safe query execution
- Transaction management with begin/commit/rollback
- AI-powered tools for SQL generation, optimization, and analysis
- Structured audit logging for compliance
- Async execution with connection pooling
Quick Start
Prerequisites
- Python 3.12+
- PostgreSQL 14+
- pip
Installation
# Clone the repository
git clone https://github.com/your-org/postgres-mcp.git
cd postgres-mcp
# Create virtual environment
python -m venv .venv
.venv\Scripts\activate # Windows
# source .venv/bin/activate # Linux/Mac
# Install dependencies
pip install -r requirements.txt
# Copy and configure environment
copy .env.example .env
# Edit .env with your database credentials
Configure .env
DATABASE_URL=postgresql+asyncpg://user:password@localhost:5432/your_db
DATABASE_HOST=localhost
DATABASE_PORT=5432
DATABASE_NAME=your_db
DATABASE_USER=your_user
DATABASE_PASSWORD=your_password
READ_ONLY_MODE=false
ENABLE_AI_SQL=true
ENABLE_AUDIT_LOG=true
Run the Server
python -m app.server
Run Tests
pytest -v
MCP Client Configuration
Claude Desktop
Add to claude_desktop_config.json:
{
"mcpServers": {
"postgres": {
"command": "python",
"args": ["-m", "app.server"],
"cwd": "/path/to/postgres-mcp",
"env": {
"DATABASE_URL": "postgresql+asyncpg://user:pass@localhost:5432/db"
}
}
}
}
Cursor / VS Code
{
"mcpServers": {
"postgres": {
"command": "python",
"args": ["-m", "app.server"],
"cwd": "/path/to/postgres-mcp"
}
}
}
Available Tools
Database Information
| Tool | Description |
|---|---|
list_databases |
List all accessible databases |
current_database |
Get current database name |
list_schemas |
List all schemas |
list_tables |
List tables in a schema |
list_views |
List views in a schema |
list_functions |
List functions in a schema |
list_indexes |
List indexes in a schema |
list_sequences |
List sequences in a schema |
list_extensions |
List installed extensions |
Schema Inspection
| Tool | Description |
|---|---|
describe_table |
Full table description |
describe_column |
Column metadata |
foreign_keys |
Foreign key relationships |
primary_keys |
Primary key columns |
unique_constraints |
Unique constraints |
check_constraints |
Check constraints |
table_size |
Table size with indexes |
database_size |
Total database size |
Query Execution
| Tool | Description |
|---|---|
execute_select |
Structured SELECT queries |
execute_insert |
Insert rows |
execute_update |
Update rows |
execute_delete |
Delete rows |
execute_query |
Raw SQL execution |
Transactions
| Tool | Description |
|---|---|
begin_transaction |
Start a transaction |
commit_transaction |
Commit changes |
rollback_transaction |
Undo changes |
Admin Tools
| Tool | Description |
|---|---|
active_connections |
List active connections |
running_queries |
List running queries |
locks |
List locks and deadlocks |
vacuum_status |
Vacuum and dead tuple info |
analyze_table |
Update table statistics |
server_version |
Get server version |
server_settings |
Get server settings |
AI Tools
| Tool | Description |
|---|---|
generate_sql |
Generate SQL from description |
explain_sql |
Human-readable query explanation |
optimize_sql |
Query optimization suggestions |
validate_sql |
Validate without executing |
detect_sql_injection |
Security analysis |
estimate_query_cost |
Cost estimation |
Security
Guardrails
The server automatically blocks dangerous operations:
DROP DATABASE/DROP ROLEALTER SYSTEMCOPY ... PROGRAMTRUNCATE(requires confirmation)pg_sleep(),pg_read_file(),pg_write_file()- Multi-statement queries
- SQL injection patterns
Read-Only Mode
When READ_ONLY_MODE=true, only SELECT and EXPLAIN are allowed.
Role-Based Access
| Role | Access Level |
|---|---|
| Viewer | Read metadata only |
| Analyst | SELECT queries + AI tools |
| Developer | INSERT/UPDATE/DELETE + transactions |
| DBA | Admin tools (connections, settings) |
| Admin | Full access |
Docker
# Build
docker build -t postgres-mcp .
# Run
docker run -p 8000:8000 \
-e DATABASE_URL=postgresql+asyncpg://user:pass@host:5432/db \
postgres-mcp
Architecture
app/
├── server.py # FastMCP server with all tool registrations
├── config.py # Pydantic Settings configuration
├── database.py # Async database connection manager
├── guards/
│ ├── sql_guard.py # SQL validation and risk classification
│ └── permissions.py # Role-based access control
├── tools/
│ ├── schema_tools.py # Database/schema inspection
│ ├── query_tools.py # CRUD query execution
│ ├── transaction_tools.py # Transaction management
│ ├── admin_tools.py # Monitoring and admin
│ └── ai_tools.py # AI-powered SQL analysis
├── services/
│ └── audit.py # Audit logging
├── models/
│ └── schemas.py # Pydantic input/output models
└── utils/
├── logging.py # Structured logging
└── helpers.py # Utilities (pagination, injection detection)
Development
# Install dev dependencies
pip install -r requirements.txt
# Run linter
ruff check app/ tests/
# Run formatter
black app/ tests/
# Run type checker
mypy app/
# Run tests with coverage
pytest --cov=app --cov-report=term-missing
Future Enhancements
- pgvector integration for vector similarity search
- Semantic search across database schemas
- RAG workflows for database documentation
- Multi-database support (MySQL, SQLite, SQL Server)
- Streaming for large result sets
- Prepared statement caching
- Query result caching with TTL
- Webhook notifications for schema changes
- GraphQL endpoint alongside MCP
- Dashboard UI for monitoring
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.