Memorizer
Provides persistent memory storage with semantic search capabilities through PostgreSQL and pgvector, enabling long-term context retention across sessions with vector-based storage, relationship tracking, and asynchronous metadata processing.
About
This MCP server provides AI assistants with persistent memory storage and semantic search capabilities through PostgreSQL with pgvector, built by Petabridge using .NET 9 and Akka.NET actors for background processing. The implementation offers vector-based memory storage with dual embeddings (full content and metadata-only), relationship tracking between memories, and asynchronous title generation and metadata embedding processing using Ollama for LLM operations. Built with web UI for memory management, OpenTelemetry integration, and Docker containerization, it serves AI agents needing long-term memory persistence, developers building conversational AI systems that require context retention across sessions, and teams wanting semantic search capabilities with tag-based filtering and similarity scoring for knowledge management workflows.
Is this your product? Claim this listing with an email at your domain to post updates.
Is this your project?
Claim this listing to manage your page, access analytics, and unlock upgrades. Verification takes 60 seconds.
Share This Project
Embed Badge
Add this badge to your README:
[](https://hifriendbot.com/ai-list/memorizer/)
