# Memorizer

> Use this tool when you need to provide AI agents with long-term memory persistence and semantic search capabilities. The Memorizer tool solves problems of context retention across sessions and knowledge management workflows by offering vector-based memory storage, relationship tracking, and asynchronous processing. It takes in memory data and outputs searchable, filterable memories with similarity scoring, ideal for conversational AI systems and teams requiring advanced knowledge management.

Canonical page: https://skillsregistry.net/skills/petabridge-memorizer  
JSON: https://api.skillsregistry.net/v1/skills/petabridge-memorizer

## Description

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.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-05-05

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/petabridge-memorizer)
- **Repository:** <https://github.com/petabridge/memorizer>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "petabridge-memorizer"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/petabridge-memorizer` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/petabridge-memorizer/pull`

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