postg-mem

MCP server to store memories in postgres

13 stars C#Servers & Infrastructure Updated Oct 24, 2025

Documentation

PostgMem

A Model Context Protocol (MCP) server implementation that provides vector memory storage using PostgreSQL and pgvector for AI applications.

Overview

PostgMem is a .NET-based service that allows AI agents to store, retrieve, and search through memories using vector embeddings. It leverages PostgreSQL with the pgvector extension to provide efficient similarity search capabilities.

Key features:

Store structured memories with vector embeddings
Retrieve memories by ID
Semantic search through memories using vector similarity
Filter search results using tags
MCP (Model Context Protocol) integration for easy use with AI agents

Technologies

.NET 9.0
PostgreSQL with pgvector extension
Model Context Protocol (MCP)
ASP.NET Core
Npgsql for PostgreSQL connectivity

Prerequisites

.NET 9.0 SDK
PostgreSQL database with pgvector extension installed
Text embedding API (default configuration uses Ollama)

Setup

Database Configuration

1. Create a PostgreSQL database for the application

2. Install the pgvector extension in your database:

sql

CREATE EXTENSION vector;

3. Create the memories table:

sql

CREATE TABLE memories (
       id UUID PRIMARY KEY,
       type TEXT NOT NULL,
       content JSONB NOT NULL,
       source TEXT NOT NULL,
       embedding VECTOR(384) NOT NULL,
       tags TEXT[] NOT NULL,
       confidence DOUBLE PRECISION NOT NULL,
       created_at TIMESTAMP WITH TIME ZONE NOT NULL,
       updated_at TIMESTAMP WITH TIME ZONE NOT NULL
   );

Environment Configuration

Configure the application settings in the `.env` file:

code

ConnectionStrings__Storage="Host=localhost;Database=mcp_memory;Username=postgres;Password=postgres"
Embeddings__ApiUrl=http://localhost:11434/
Embeddings__Model=all-minilm:33m-l12-v2-fp16

`ConnectionStrings__Storage`: PostgreSQL connection string
`Embeddings__ApiUrl`: URL of your embedding API (defaults to Ollama)
`Embeddings__Model`: The embedding model to use

Running the Application

1. Navigate to the PostgMem directory

2. Run the application:

code

dotnet run

3. The MCP server will be available at `http://localhost:5000` by default

MCP Tools

The following MCP tools are available:

Store

Store a new memory in the database.

Parameters:

`type` (string): The type of memory (e.g., 'conversation', 'document', etc.)
`content` (string): The content of the memory as a JSON object
`source` (string): The source of the memory (e.g., 'user', 'system', etc.)
`tags` (string[]): Optional tags to categorize the memory
`confidence` (double): Confidence score for the memory (0.0 to 1.0)

Search

Search for memories similar to the provided text.

Parameters:

`query` (string): The text to search for similar memories
`limit` (int): Maximum number of results to return (default: 10)
`minSimilarity` (double): Minimum similarity threshold (0.0 to 1.0) (default: 0.7)
`filterTags` (string[]): Optional tags to filter memories