Memories

A memory is one durable thing worth keeping: a decision, an insight, a fact, a procedure, an experience. Each memory should stand on its own, readable without the full conversation that produced it.

Memories are the core unit of Nowledge Mem. Search, the knowledge graph, crystals, daily briefings, and connected tools all become more useful because memories exist underneath them.

The First Useful Memory

If you are new, do not overthink structure first. Save one real thing such as:

• a decision you made
• a lesson you learned
• a workflow you repeat

Then ask for it back in the Timeline. Once that works, this whole page becomes much easier to understand.

Anatomy of a Memory

Importance Scale

The default is 0.5. AI tools and background intelligence use this score to prioritize what surfaces in search results and daily briefings.

Labels

Standard categories:

New memories are labeled automatically when created. The system assigns 2–4 labels based on content and reuses your existing labels to keep the taxonomy consistent. You can always edit, add, or remove labels afterward.

You can also create custom labels. Labels are lowercase and hyphenated (api-design, team-standup). Filter by label in the Memories view to focus on a specific domain.

Creating Memories

In the Timeline

Type into the input at the top and press Enter. AI classifies your intent automatically:

• A thought becomes a memory with auto-generated title and labels
• A question gets answered from your existing knowledge
• A URL gets fetched, parsed, and indexed
• A file gets parsed and stored

See Getting Started for the full onboarding walkthrough.

From AI Conversations

The browser extension captures memories from supported web AI chat platforms:

• Auto-Capture monitors conversations and saves what matters autonomously
• Manual Distill lets you trigger capture on a specific conversation

From Threads

Import a conversation, then distill it into individual memories. Each extracted memory gets its own title, labels, and importance score. This is how hours of AI conversation become searchable, connected knowledge. See Threads for the full workflow.

From AI Tools

Connected agents can read, search, and preserve durable knowledge while you work. The exact path depends on the integration surface you chose:

The best-integrated setups do more than expose memory_add: they also teach the agent when to search first and when to update an existing memory instead of creating a duplicate.

Via CLI

# Add a memory with auto-generated title
nmem m add "We chose PostgreSQL for the new service because of jsonb support"

# Add with explicit title and labels
nmem m add "PostgreSQL chosen for jsonb support and team familiarity" \
  --title "Database Decision: PostgreSQL" \
  --labels "decision,infrastructure" \
  --importance 0.8

Via API

curl -X POST http://127.0.0.1:14242/memories \
  -H "Content-Type: application/json" \
  -d '{
    "content": "We chose PostgreSQL for the new service",
    "title": "Database Decision",
    "labels": ["decision", "infrastructure"],
    "importance": 0.8
  }'

See the API Reference for the full schema.

Searching Memories

In the App

Open memory search with Cmd + K (macOS) or Ctrl + K (Windows/Linux). Three search modes work together:

• Semantic finds memories by meaning, so searching "design patterns" finds memories about "architectural approaches"
• Keyword does exact match for specific terms
• Graph discovers memories through entity connections and topic clusters

Press Cmd + Shift + K from any application to search without opening Nowledge Mem.

From AI Tools

Connected agents search through their native integration, shared workflow package, or MCP tools. When a topic might connect to prior work, the best-integrated surfaces search your knowledge base without waiting for an explicit prompt.

Via CLI

# Semantic search
nmem m search "authentication patterns"

# JSON output for scripting
nmem --json m search "API design" | jq '.memories[0].content'

Editing and Organizing

Update a Memory

Click any memory in the Memories view to edit its content, title, labels, or importance. Changes take effect immediately.

Via CLI:

# Update importance
nmem m update <memory-id> --importance 0.9

# Update labels
nmem m update <memory-id> --labels "decision,infrastructure,critical"

Delete a Memory

Delete from the memory detail view, or via CLI:

nmem m delete <memory-id>

How Memories Connect

When Background Intelligence is enabled, memories grow connections automatically:

• Knowledge Graph. Every memory becomes a node. The system extracts entities (people, technologies, concepts) and maps relationships. Search "distributed systems" and find your memory about "Node.js microservices". The words don't match, the meaning does.

• Knowledge Evolution. Save something new about a topic you've written about before, and the system creates a version link: replaces, enriches, confirms, or challenges. Trace how your understanding of any topic changed over time.

• Crystals. When enough memories cover the same ground, they get synthesized into a reference article. Sources are cited. When you save related information later, the crystal updates.

• Working Memory. Each morning, a briefing lands at ~/ai-now/memory.md drawing from your recent and important memories. Your AI tools read it at session start.

See Background Intelligence for the full guide on how these work.

Where Memories Come From

MCP Tools

Next Steps

• Threads: Import and distill AI conversations into memories
• Library: Import documents alongside your memories
• AI Now: Personal AI with full access to your knowledge base
• Background Intelligence: How memories grow connections automatically
• Browser Extension: Capture memories from web AI conversations
• Integrations: Connect your AI tools through native integrations, reusable packages, or MCP