By phanvuhoang
Reflex-based memory system for AI agents — stores experiences as interconnected neurons and recalls them through spreading activation, mimicking how the human brain works.
Comprehensive memory quality review across 6 dimensions: purity, freshness, coverage, clarity, relevance, and structure. Generates prioritized findings with specific memory references and actionable recommendations.
Evidence-based memory optimization from real usage patterns. Analyzes recall performance, identifies bottlenecks, suggests consolidation/pruning/enrichment, and tracks improvement over time via checkpoint Q&A.
Structured memory creation workflow. Converts messy notes, conversations, and unstructured thoughts into well-typed, tagged, confidence-scored memories. Uses 1-question-at-a-time clarification to avoid cognitive overload.
Uses power tools
Uses Bash, Write, or Edit tools
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Reflex-based memory system for AI agents — retrieval through activation, not search.
NeuralMemory stores experiences as interconnected neurons and recalls them through spreading activation, mimicking how the human brain works. Instead of searching a database, memories surface through associative recall — activating related concepts until the relevant memory emerges.
28 MCP tools · 11 memory types · 24 synapse types · Schema v20 · 2860+ tests
| Aspect | RAG / Vector Search | NeuralMemory |
|---|---|---|
| Model | Search engine | Human brain |
| LLM/Embedding | Required (embedding API calls) | None — pure algorithmic graph traversal |
| Query | "Find similar text" | "Recall through association" |
| Structure | Flat chunks + embeddings | Neural graph + synapses |
| Relationships | None (just similarity) | Explicit: CAUSED_BY, LEADS_TO, RESOLVED_BY, etc. |
| Temporal | Timestamp filter | Time as first-class neurons |
| Multi-hop | Multiple queries needed | Natural graph traversal |
| Lifecycle | Static | Decay, reinforcement, consolidation |
| API Cost | ~$0.02/1K queries | $0.00 — fully offline |
Example: "Why did Tuesday's outage happen?"
outage ← CAUSED_BY ← JWT ← SUGGESTED_BY ← Alice → full causal chainpip install neural-memory
With optional features:
pip install neural-memory[server] # FastAPI server + dashboard
pip install neural-memory[extract] # PDF/DOCX/PPTX/HTML/XLSX extraction
pip install neural-memory[nlp-vi] # Vietnamese NLP
pip install neural-memory[all] # All features
/plugin marketplace add nhadaututtheky/neural-memory
/plugin install neural-memory@neural-memory-marketplace
That's it. MCP server, skills, commands, and agent are all configured automatically via uvx.
pip install neural-memory
npm install -g @neuralmemory/openclaw-plugin
Then set the memory slot in ~/.openclaw/openclaw.json:
{ "plugins": { "slots": { "memory": "neuralmemory" } } }
Restart the gateway. See the full setup guide.
pip install neural-memory
Then add to your editor's MCP config (Cursor: .cursor/mcp.json, Windsurf: ~/.codeium/windsurf/mcp_config.json):
{
"mcpServers": {
"neural-memory": {
"command": "nmem-mcp"
}
}
}
The editor spawns nmem-mcp automatically via stdio — no manual server start needed. No nmem init needed — auto-initializes on first use.
# Store memories (type auto-detected)
nmem remember "Fixed auth bug with null check in login.py:42"
nmem remember "We decided to use PostgreSQL" --type decision
nmem todo "Review PR #123" --priority 7
# Recall memories
nmem recall "auth bug"
nmem recall "database decision" --depth 2
# Shortcuts
nmem a "quick note" # Short for remember
nmem q "auth" # Short for recall
nmem last 5 # Last 5 memories
nmem today # Today's memories
# Get context for AI injection
nmem context --limit 10 --json
# Brain management
nmem brain list
nmem brain create work
nmem brain use work
nmem brain health
nmem brain export -o backup.json
nmem brain import backup.json
# Codebase indexing
nmem index src/ # Index code into neural memory
# Memory lifecycle
nmem decay # Apply forgetting curve
nmem consolidate # Prune, merge, summarize
nmem cleanup # Remove expired memories
# Visual tools
nmem serve # Start FastAPI server
# Then open http://localhost:8000/ui for React dashboard
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