Multi-Tenant PostgreSQL MCP Server

Multi-Tenant PostgreSQL MCP Server

Enables read-only access to PostgreSQL databases with multi-tenant support, allowing users to query data, explore schemas, inspect table structures, and view function definitions across different tenant schemas safely.

Category
Visit Server

README

Multi-Tenant PostgreSQL MCP Server

A comprehensive, read-only Model Context Protocol (MCP) server for PostgreSQL databases with advanced multi-tenant support, schema introspection, and query capabilities.

Features

  • 🔒 Read-only by design - All queries run in read-only transactions for safety
  • 🏢 Multi-tenant support - Access tables and functions across different schemas
  • 🔍 Advanced schema introspection - Detailed table structures, constraints, indexes, and DDL
  • 🔧 Function definitions - Complete function metadata and source code access
  • 📊 Flexible querying - Execute SQL queries with optional schema context
  • 🌐 Network-ready - Connect to local or remote PostgreSQL instances

Installation

Via npm (recommended)

npm install -g @ahmetkca/mcp-server-postgres

Via npx (no installation required)

Run directly (no install)

npx @ahmetkca/mcp-server-postgres "postgres://user:password@host:port/database"

From source

git clone https://github.com/ahmetkca/mcp-server-postgres.git
cd mcp-server-postgres
npm install
npm run build

Usage

Command Line

With global installation:

mcp-server-postgres "postgres://user:password@host:port/database"

With npx (no installation required)

Direct execution (npx)

npx @ahmetkca/mcp-server-postgres "postgres://user:password@host:port/database"

With Claude Desktop

Add to your Claude Desktop MCP configuration (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

Option 1: Using npx (recommended - no installation required):

{
  "mcpServers": {
    "postgres-multitenant": {
      "command": "npx",
      "args": ["-y", "@ahmetkca/mcp-server-postgres", "postgres://user:password@localhost:5432/mydb"]
    }
  }
}

Option 2: Using global installation

Global install

{
  "mcpServers": {
    "postgres-multitenant": {
      "command": "mcp-server-postgres",
      "args": ["postgres://user:password@localhost:5432/mydb"]
    }
  }
}

With other MCP clients

The server uses stdio transport, so it can be used with any MCP client that supports subprocess communication:

# Direct execution
npx @ahmetkca/mcp-server-postgres "postgres://connection-string"

# Or with global install
mcp-server-postgres "postgres://connection-string"

Connection String Examples

Local PostgreSQL

mcp-server-postgres "postgres://user:password@localhost:5432/mydb"

Remote PostgreSQL

mcp-server-postgres "postgres://user:password@db.example.com:5432/mydb"

AWS RDS

mcp-server-postgres "postgres://user:password@mydb.abc123.us-east-1.rds.amazonaws.com:5432/mydb"

Google Cloud SQL

mcp-server-postgres "postgres://user:password@1.2.3.4:5432/mydb"

With SSL (recommended for production)

mcp-server-postgres "postgres://user:password@host:5432/mydb?sslmode=require"

Available Resources

Schema Overview

  • URI Pattern: pg-schema://{schemaName}/overview
  • Description: High-level overview of a schema including counts (tables, views, functions) and quick links (URIs) to table structures and function definitions for drill-down
  • Example: pg-schema://public/overview
  • Completions: Supports typeahead for schemaName

Table Structures

  • URI Pattern: pg-table://{schemaName}/{tableName}/structure
  • Description: Comprehensive table metadata including columns, constraints, indexes, and DDL
  • Example: pg-table://public/users/structure

Function Definitions

  • URI Pattern: pg-func://{schemaName}/{functionName}/(identityArgs)/definition
  • Description: Complete function metadata, parameters, return types, and source code
  • Example: pg-func://public/calculate_total/()/definition
  • Overloads: identityArgs is the canonical PostgreSQL identity argument list (e.g. (integer,integer)). Example overload: pg-func://public/add/(integer,integer)/definition

Available Tools

1. Multi-Tenant Database Query Tool

Execute read-only SQL queries to retrieve, analyze, and explore PostgreSQL data across multiple tenant schemas. Supports complex SQL including JOINs, CTEs, window functions, and aggregations. All queries run in read-only transactions for safety.

Parameters:

  • sql (string, required): The SQL query to execute. Can be any valid PostgreSQL SELECT statement including complex queries with JOINs, CTEs, window functions, aggregations, etc. Will be executed in a read-only transaction for safety.
  • schema (string, optional): Optional schema name (tenant) to set as search_path before executing the query. When specified, unqualified table names will resolve to tables in this schema. Use this for tenant-specific queries.
  • explain (boolean, optional): Set to true to return the query execution plan instead of query results. Useful for performance analysis and optimization. Returns PostgreSQL EXPLAIN output in JSON format.

Examples:

-- Simple query with default schema
SELECT * FROM users LIMIT 10;

-- Complex query with JOINs and aggregations
SELECT 
  u.name, 
  COUNT(o.id) as order_count,
  SUM(o.total) as total_spent,
  AVG(o.total) as avg_order_value
FROM users u 
LEFT JOIN orders o ON u.id = o.user_id 
WHERE u.created_at > '2024-01-01'
GROUP BY u.id, u.name
ORDER BY total_spent DESC;

-- Query with CTE and window functions
WITH monthly_sales AS (
  SELECT 
    DATE_TRUNC('month', created_at) as month,
    SUM(total) as monthly_total,
    LAG(SUM(total)) OVER (ORDER BY DATE_TRUNC('month', created_at)) as prev_month
  FROM orders 
  GROUP BY DATE_TRUNC('month', created_at)
)
SELECT 
  month,
  monthly_total,
  ROUND(((monthly_total - prev_month) / prev_month * 100)::numeric, 2) as growth_rate
FROM monthly_sales
WHERE prev_month IS NOT NULL;

-- Tenant-specific query (set schema parameter to "tenant_a")
SELECT * FROM orders WHERE status = 'pending';

-- Performance analysis (set explain parameter to true)
SELECT u.*, o.total FROM users u JOIN orders o ON u.id = o.user_id;

2. List Database Schemas

Discover all available database schemas (tenants) with statistics including table and function counts. Use this to explore the multi-tenant structure, identify available tenants, or get an overview of database organization.

Parameters:

  • include_system (boolean, optional): Set to true to include PostgreSQL system schemas (information_schema, pg_catalog, pg_toast) in the results. Default false shows only user/tenant schemas. Use true for administrative or debugging purposes.

Use Cases:

  • Explore multi-tenant database structure
  • Identify available tenant schemas
  • Get overview of database organization
  • Administrative schema analysis

3. Describe Schema

Get comprehensive information about a specific database schema (tenant) including detailed statistics, all tables, views, functions, and custom types. Use this to understand a tenant's database structure, analyze schema composition, or prepare for schema-specific operations.

Parameters:

  • schema_name (string, required): Name of the database schema (tenant) to analyze. Must be an exact schema name from the database. Use list-schemas tool first to discover available schema names.

Returns:

  • Schema statistics (table count, view count, function count, type count)
  • Detailed table information with column counts
  • Function definitions and metadata
  • Organized metadata perfect for schema analysis and documentation

Multi-Tenant Architecture

This server is designed for multi-tenant PostgreSQL setups where:

  • Different tenants have separate schemas (e.g., tenant_a, tenant_b, public)
  • Each schema contains tenant-specific tables and functions
  • You need to query across different tenant contexts

Example Multi-Tenant Usage

-- List all schemas
-- Use "list-schemas" tool

-- Describe a specific tenant schema
-- Use "describe-schema" tool with schema_name: "tenant_a"

-- Query tenant-specific data
-- Use "query" tool with schema: "tenant_a"
SELECT * FROM orders WHERE status = 'pending';

-- Get table structure for a tenant
-- Access resource: pg-table://tenant_a/orders/structure

Security Features

  • Read-only transactions: All queries are wrapped in BEGIN TRANSACTION READ ONLY
  • No data modification: INSERT, UPDATE, DELETE, and DDL operations are blocked
  • Schema isolation: Optional schema context prevents cross-tenant data access
  • Connection pooling: Efficient resource management with automatic cleanup

Development

Prerequisites

  • Node.js 18+
  • PostgreSQL database (local or remote)
  • TypeScript knowledge (for contributions)

Setup

git clone https://github.com/ahmetkca/mcp-server-postgres.git
cd mcp-server-postgres
npm install

Development Commands

npm run dev          # Watch mode for development
npm run build        # Build for production
npm run start        # Start the built server

Testing

Start the server with a test database

npm run build
npm start "postgres://user:password@localhost:5432/testdb"

In another terminal, test with MCP Inspector

npx @modelcontextprotocol/inspector

Troubleshooting

Connection Issues

  • Verify your PostgreSQL connection string
  • Check network connectivity to the database
  • Ensure the database user has SELECT permissions
  • For remote connections, verify firewall settings

Permission Issues

  • The database user needs SELECT permissions on:
    • All tables you want to query
    • information_schema views
    • pg_catalog system tables (for function definitions)

Schema Access

  • Ensure the database user has USAGE permission on schemas
  • For multi-tenant setups, grant access to relevant tenant schemas

Contributing

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

Changelog

v1.1.0 - 2025-08-07

  • Adopt custom resource URI schemes:
    • Tables: pg-table://{schemaName}/{tableName}/structure
    • Functions: pg-func://{schemaName}/{functionName}/(identityArgs)/definition
  • Per-overload function resources using canonical identityArgs to disambiguate overloads
  • Deterministic, deduplicated resource listings using DISTINCT ON and stable ordering
  • Exact overload resolution via regprocedure/OID for function metadata
  • README updated to reflect new URI schemes and best practices
  • TypeScript build fixes: NodeNext ESM config, top-level await, and pg Pool named import

v1.0.0

  • Initial release
  • Multi-tenant PostgreSQL support
  • Advanced schema introspection
  • Function definition access
  • Read-only query execution
  • Comprehensive documentation

Examples: listing and reading

Below are minimal examples of how resources appear in clients and how to read them. Actual UX varies by MCP client, but the URIs and fields are the same.

1) Listing resources (conceptual)

Clients request a list from the server and render entries like:

name: public
uri:  pg-schema://public/overview
—
name: public.users
uri:  pg-table://public/users/structure
—
name: tenant_a.app_event
uri:  pg-table://tenant_a/app_event/structure
—
name: public.add(integer,integer)
uri:  pg-func://public/add/(integer,integer)/definition
—
name: public.add(text,text)
uri:  pg-func://public/add/(text,text)/definition

2) Reading a schema overview

  • Select: pg-schema://public/overview
  • The client sends a read request and receives JSON with statistics and quick links (URIs) to tables and functions.

JSON-RPC (abridged) example over stdio:

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "resources/read",
  "params": { "uri": "pg-schema://public/overview" }
}

Response (shape):

{
  "jsonrpc": "2.0",
  "id": 1,
  "result": {
    "contents": [
      {
        "uri": "pg-schema://public/overview",
        "mimeType": "application/json",
        "text": "{ ... statistics, tables.first_100 [{name, uri}], functions.first_100 [{name, uri}] ... }"
      }
    ]
  }
}

2) Reading a table structure

  • Select: pg-table://tenant_a/app_event/structure
  • Client sends a read request and receives JSON describing columns, constraints, indexes, relationships, and DDL.

JSON-RPC (abridged) example over stdio:

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "resources/read",
  "params": { "uri": "pg-table://tenant_a/app_event/structure" }
}

Response (shape):

{
  "jsonrpc": "2.0",
  "id": 1,
  "result": {
    "contents": [
      {
        "uri": "pg-table://tenant_a/app_event/structure",
        "mimeType": "application/json",
        "text": "{ ... columns, constraints, indexes, ddl ... }"
      }
    ]
  }
}

3) Reading a specific function overload

  • Select: pg-func://public/add/(integer,integer)/definition
  • The server resolves the exact overload by regprocedure and returns the definition.

JSON-RPC (abridged) example:

{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "resources/read",
  "params": { "uri": "pg-func://public/add/(integer,integer)/definition" }
}

Response (shape):

{
  "jsonrpc": "2.0",
  "id": 2,
  "result": {
    "contents": [
      {
        "uri": "pg-func://public/add/(integer,integer)/definition",
        "mimeType": "application/json",
        "text": "{ ... parameters, return_type, language, volatility, security, source, ddl ... }"
      }
    ]
  }
}

Tips

  • Choose the exact overload by picking the URI that includes the identity args in parentheses.
  • All identifiers in URIs are URL-encoded; clients decode them before invoking the handler.
  • Lists are deduplicated and ordered for a clean browsing experience.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Recommended Servers

playwright-mcp

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.

Official
Featured
TypeScript
Magic Component Platform (MCP)

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.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

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.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

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.

Official
Featured
TypeScript
Kagi MCP Server

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.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

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.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured