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Memorizer V1

AI community

Description

Vector-search powered agent memory MCP server

Installation

This entry records only its repository, not the path inside it, so there is no exact command to give. Open the source below and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

README

Memorizer

[![Docker Pulls](https://img.shields.io/docker/pulls/petabridge/memorizer)](https://hub.docker.com/r/petabridge/memorizer) ![GitHub License](https://img.shields.io/github/license/petabridge/memorizer) ![GitHub Actions Workflow Status](https://img.shields.io/github/actions/workflow/status/petabridge/memorizer/pr_validation.yml) ![GitHub Release](https://img.shields.io/github/v/release/petabridge/memorizer)

Memorizer 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.

![Memorizer - Memory List](https://raw.githubusercontent.com/petabridge/memorizer/refs/heads/dev/docs/images/memory-list-dark.png)

Key features:

  • Workspaces & Projects - Organize memories into hierarchical workspaces and projects with status tracking
  • Store structured memories with vector embeddings
  • Retrieve memories by ID
  • Semantic search through memories using vector similarity
  • Filter search results using tags
  • Edit memory content with automatic versioning and change tracking
  • Update memory metadata (title, type, tags, confidence) independently
  • Revert memories to previous versions with full audit trail
  • Create relationships between memories to form knowledge graphs
  • Web UI for manually adding, editing, deleting, viewing memories, and managing versions
  • Provider Settings - Configure embedding and LLM providers through the UI (Ollama, OpenAI, and compatible APIs)
  • MCP (Model Context Protocol) integration for easy use with AI agents
  • Light & Dark theme support

![Memorizer - Workspace Detail](https://raw.githubusercontent.com/petabridge/memorizer/refs/heads/dev/docs/images/workspace-detail-dark.png)

Technologies

  • .NET 10.0
  • PostgreSQL with pgvector extension
  • Model Context Protocol (MCP)
  • ASP.NET Core
  • Akka.NET for background jobs, such as re-embedding memorie