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Postgres Mcp Tools
What is Postgres Mcp Tools
Postgres-MCP-Tools is a PostgreSQL-based memory system designed for AI applications, featuring vector search capabilities and integration with Claude through the Model Context Protocol (MCP).
Use cases
Use cases include implementing AI-driven chat interfaces, enhancing search functionalities in applications, and managing user context in conversational agents.
How to use
To use postgres-mcp-tools, install it globally via npm, start PostgreSQL and the MCP server using Docker, and configure your environment variables as needed. Detailed instructions can be found in the provided documentation.
Key features
Key features include vector search for semantic content retrieval, support for multiple embedding models (OpenAI, Anthropic), MCP integration for direct connection to Claude, a REST API for programmatic access, and Docker support for easy deployment.
Where to use
Postgres-MCP-Tools is suitable for AI applications that require semantic search capabilities, such as chatbots, recommendation systems, and any system needing persistent memory for user interactions.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Postgres Mcp Tools
Postgres-MCP-Tools is a PostgreSQL-based memory system designed for AI applications, featuring vector search capabilities and integration with Claude through the Model Context Protocol (MCP).
Use cases
Use cases include implementing AI-driven chat interfaces, enhancing search functionalities in applications, and managing user context in conversational agents.
How to use
To use postgres-mcp-tools, install it globally via npm, start PostgreSQL and the MCP server using Docker, and configure your environment variables as needed. Detailed instructions can be found in the provided documentation.
Key features
Key features include vector search for semantic content retrieval, support for multiple embedding models (OpenAI, Anthropic), MCP integration for direct connection to Claude, a REST API for programmatic access, and Docker support for easy deployment.
Where to use
Postgres-MCP-Tools is suitable for AI applications that require semantic search capabilities, such as chatbots, recommendation systems, and any system needing persistent memory for user interactions.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
PostgreSQL MCP Tools
PostgreSQL-based memory system with vector search capabilities for AI applications, including MCP integration for Claude.
Overview
This package provides a memory system built on PostgreSQL with pgvector that enables:
- Storage and retrieval of vectorized content for semantic search
- Persistent memory across sessions
- Integration with Claude through the Model Context Protocol (MCP)
- Support for multiple embedding models (OpenAI, Anthropic, or mock for testing)
Installation
# Install globally (preferred)
npm install -g postgres-mcp-tools
# If you encounter dependency errors, try:
npm install -g postgres-mcp-tools --force --no-save
# If you're still having issues, you can install from the GitHub repo:
git clone https://github.com/ssmanji89/postgres-mcp-tools.git
cd postgres-mcp-tools
npm install
npm run setup-mcp-sdk
npm link
Quick Start
For detailed installation instructions including troubleshooting, see INSTALLATION.md.
Start PostgreSQL
# Start PostgreSQL in Docker
docker-compose up -d postgres
Start the MCP Server
# Start the MCP server
docker-compose up -d mcp-server
Test the Robust Transport
# Verify the robust transport functionality
npm run test-transport
Configure Claude Desktop
See CLAUDE_DESKTOP_SETUP.md for detailed instructions.
Features
- Vector Search: Store and search content using vector embeddings
- Multiple Embedding Models: Support for OpenAI, Anthropic, or mock embeddings
- MCP Integration: Connect directly to Claude via the Model Context Protocol
- REST API: Access memory programmatically through HTTP endpoints
- Docker Support: Run everything in containers for easy deployment
Configuration
Configuration is managed through environment variables or command-line arguments:
POSTGRES_HOST: PostgreSQL host (default: localhost)POSTGRES_PORT: PostgreSQL port (default: 5432)POSTGRES_USER: PostgreSQL username (default: memory_user)POSTGRES_PASSWORD: PostgreSQL passwordPOSTGRES_DB: PostgreSQL database name (default: memory_db)EMBEDDING_MODEL: Embedding model to use: “openai”, “anthropic”, or “mock” (default: mock)OPENAI_API_KEY: OpenAI API key (if using OpenAI embeddings)ANTHROPIC_API_KEY: Anthropic API key (if using Anthropic embeddings)MCP_SERVER_PORT: MCP server port (default: 3000)HTTP_PORT: HTTP API port (default: 8080)
Docker Setup
The easiest way to run PostgreSQL MCP Tools is using Docker:
# Start everything
docker-compose up -d
# Stop everything
docker-compose down
Development
# Install dependencies
npm install
# Install test dependencies
npm run update-deps
# Build the server
npm run build-server
# Run minimal tests (recommended)
npm run test:basic
# Run transport tests (may require configuration)
npm run test:transport
Note: The test setup is configured for ESM compatibility in a primarily ESM project. If you encounter issues, try the alternate test configuration with
npm run test:alt.
See tests/README.md for more information on testing.
Claude Desktop Integration
As of version 1.0.9, PostgreSQL MCP Tools now properly integrates with Claude Desktop by ensuring all debug logs go to stderr instead of stdout, maintaining proper JSON-RPC protocol communication.
Latest Release: v1.0.14 (2025-03-23)
We’ve implemented a production-ready robust transport layer that handles non-JSON messages gracefully and fixed critical logging issues that were causing server crashes.
Logging System Improvements
- Fixed logs directory creation issue that was causing server crashes
- Added prestart script to ensure logs directory exists before server starts
- Improved error handling in the logger configuration
Robust Transport Layer
Key improvements:
- Added error handling for non-JSON messages in the transport layer
- Implemented a robust HTTP transport that doesn’t crash on invalid input
- Added global error handlers to prevent unhandled exceptions and rejections
- Improved logging to help diagnose issues
- Properly handles bidirectional communication with clients
- Maintains session information required by the MCP protocol
- Updated Claude Desktop configuration format for proper port settings
For detailed information about the robust transport implementation, see ROBUST_TRANSPORT.md.
If you previously experienced JSON parsing errors when starting the server, this update should resolve those issues.
See full RELEASE_NOTES.md for all changes.
Upgrading to v1.0.14
If you’re upgrading from a previous version, run:
# First, remove the old version
npm uninstall -g postgres-mcp-tools
# Then install the new version
npm install -g postgres-mcp-tools
# If you encounter dependency errors, try:
npm install -g postgres-mcp-tools --force --no-save
# Or install from the GitHub repo:
git clone https://github.com/ssmanji89/postgres-mcp-tools.git
cd postgres-mcp-tools
npm install
npm run setup-mcp-sdk
npm link
Then update your Claude Desktop configuration as described in CLAUDE_DESKTOP_SETUP.md and restart the MCP server:
npm run start-server
License
MIT
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.










