PostgMem is a .NET-based MCP server that enables AI agents to store, search, and retrieve memories via vector embeddings in PostgreSQL with pgvector extension.
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Created by:
Apr 25 2025
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What is PostgMem?
PostgMem provides a comprehensive solution for managing memories in AI applications. It allows structured memory storage with vector embeddings, enabling semantic search and retrieval through similarity matching. Integrating with PostgreSQL and the pgvector extension, it supports efficient queries, filtering by tags, and storing diverse memory types. Built on .NET technology, it offers easy MCP protocol compatibility for seamless integration with AI agents and services, making it suitable for applications requiring dynamic memory management and fast retrieval.
Who will use PostgMem?
- AI developers
- Data scientists
- Researchers
- AI application architects
How to use the PostgMem?
- Step1: Setup PostgreSQL with pgvector extension installed
- Step2: Configure environment variables with database connection details
- Step3: Run the PostgMem application
- Step4: Use MCP Store, Search, Get, or Delete tools for memory management
PostgMem's Core Features & Benefits
The Core Features
- Store memory with vectors and metadata
- Retrieve memory by ID
- Semantic search with similarity threshold
- Filter memories with tags
The Benefits
- Efficient vector similarity search
- Easy integration with AI workflows
- Structured and flexible memory management
PostgMem's Main Use Cases & Applications
- AI agent context management
- Semantic content retrieval
- Memory-driven AI personalization
- Research data storage and analysis