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.

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

• .NET 10.0
• PostgreSQL with pgvector extension
• Model Context Protocol (MCP)
• ASP.NET Core
• Akka.NET for background jobs, such as re-embedding memories if you change algorithms
• Npgsql for PostgreSQL connectivity

• Feature Gallery (Screenshots)
• Configuration & Advanced Setup
• Security Configuration
• Embedding Models & Dimensions
• Embedding Dimension Migration
• Local Development
• Schema Migrations
• Architecture Decision Records

The easiest way to get started is using the pre-built Docker image and our docker-compose.yml file:

docker-compose up -d

This will:

• Download and run the latest petabridge/memorizer image from Docker Hub
• Start PostgreSQL with pgvector (port 5432)
• Start PgAdmin (port 5050)
• Start Ollama (port 11434)
• Start Memorizer API (port 5000)

View the Memorizer Web UI on http://localhost:5000.

If you want to build and run from source:

• Docker and Docker Compose
• .NET 10.0 SDK

# From solution root directory
# Build and publish the .NET container
dotnet publish -c Release /t:PublishContainer

This creates a container image named memorizer:latest.

docker-compose -f docker-compose.local.yml up -d

This starts the same services but uses your locally built image.

Before pulling the new Memorizer 2.0 image, create a PostgreSQL dump of your existing database:

# Create a full database backup
docker exec postgmem-postgres pg_dump -U postgres postgmem > memorizer-backup-$(date +%Y%m%d).sql

# Or use pg_dump with compression
docker exec postgmem-postgres pg_dump -U postgres -Fc postgmem > memorizer-backup-$(date +%Y%m%d).dump

To restore from a backup if needed:

# Restore from SQL dump
docker exec -i postgmem-postgres psql -U postgres postgmem < memorizer-backup-20250207.sql

# Or restore from compressed dump
docker exec -i postgmem-postgres pg_restore -U postgres -d postgmem memorizer-backup-20250207.dump

# make sure you have created a backup before starting here
git pull
docker-compose down
docker-compose pull memorizer
docker-compose up -d

• MCP endpoint moved from / to /mcp. Update your MCP client configurations from http://localhost:5000 to http://localhost:5000/mcp.
• Web UI moved from /ui to /. The Web UI is now at the root path.
• New database tables: Workspaces, projects, provider settings, data migrations, and archetype tracking are added automatically on first startup.
• Existing memories are preserved: All your V1 memories will continue to work. They will appear as "Unfiled" until you organize them into workspaces and projects.

To use Memorizer with any MCP-compatible client, add the following to your configuration (e.g., mcp.json):

{
  "memorizer": {
    "url": "http://localhost:5000/mcp"
  }
}

This uses the modern Streamable HTTP transport (MCP spec 2025-03-26+). Note that the MCP endpoint is at /mcp (changed from / in 2.0).

Memorizer includes a web-based user interface for managing memories through your browser.

Once the application is running (via docker-compose up -d), you can access the Web UI at:

http://localhost:5000/

• Memory Management: Create, view, edit, and delete memories with full CRUD operations
• Version Control: View version history, compare versions with visual diffs, and revert to previous versions
• Search & Filter: Search memories using semantic similarity and filter by tags
• Statistics Dashboard: View memory counts, tag distributions, and system statistics
• MCP Configuration: Get the MCP configuration JSON for connecting clients at /mcp-config

The Web UI provides a user-friendly interface for all Memorizer functionality, making it easy to manage your AI agent's memory without needing to use the MCP tools directly.

You have access to a long-term memory system via the Model Context Protocol (MCP) at the endpoint memorizer. Use the following tools:

Storage & Retrieval:

• store: Store a new memory. Parameters: type, text (markdown), source, title, tags, confidence, relatedTo (optional, memory ID), relationshipType (optional).
• searchMemories: Search for similar memories using semantic similarity. Parameters: query, limit, minSimilarity, filterTags.
• get: Retrieve a memory by ID. Parameters: id, includeVersionHistory, versionNumber.
• getMany: Retrieve multiple memories by their IDs. Parameter: ids (list of IDs).
• delete: Delete a memory by ID. Parameter: id.

Editing & Updates:

• edit: Edit memory content using find-and-replace (ideal for checking off to-do items, updating sections). Parameters: id, old_text, new_text, replace_all.
• updateMetadata: Update memory metadata (title, type, tags, confidence) without changing content. Parameters: id, title, type, tags, confidence.

Relationships & Versioning:

• createRelationship: Create a relationship between two memories. Parameters: fromId, toId, type (e.g., 'example-of', 'explains', 'related-to').
• revertToVersion: Revert a memory to a previous version. Parameters: id, versionNumber, changedBy.

All edits and updates are automatically versioned, allowing you to track changes and revert if needed. Use these tools to remember, recall, edit, relate, and manage information as needed to assist the user.

MIT

Made with ❤️ by Petabridge

Originally forked from Dario Griffo's postg-mem server