neural-memory

neural-memory

Enables AI agents to persist memories across sessions and recall them through graph-traversal spreading activation over interconnected neurons with explicit relationship types, supporting multi-hop reasoning fully offline without embedding API costs.

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NeuralMemory

GitHub stars PyPI Downloads CI Python 3.11+ License: MIT VS Code OpenClaw Plugin

Your AI agent forgets everything between sessions. Neural Memory gives it a brain.

<p align="center"> <strong><a href="https://neuralmemory.theio.vn">Website</a></strong> · <a href="https://neuralmemory.theio.vn/guides/quickstart-guide/">Quickstart</a> · <a href="https://neuralmemory.theio.vn/api/mcp-tools/">MCP Tools</a> · <a href="https://neuralmemory.theio.vn/landing/pro-landing.html">Pro</a> · <a href="https://neuralmemory.theio.vn/changelog/">Changelog</a> </p>

<p align="center"> <img src="docs/assets/images/hero-brain.svg" alt="Neural Memory — spreading activation" width="720"/> </p>

Memories are stored as interconnected neurons and recalled through spreading activation — the same way the human brain works. No vector database. No API calls. No monthly embedding bill.

pip install neural-memory

Restart your AI tool. Your agent now remembers — no init needed, the MCP server auto-initializes on first use.

Already installed? nmem update upgrades in place and detects whether you installed via pip or from source. nmem update --check only reports what is available.

The CLI is nmem (or the longer neural-memory). There is no nm binary.


3 Tools. That's It.

63 MCP tools are available, but you only need three:

Tool What it does
nmem_remember Store a memory — auto-detects type, tags, and connections
nmem_recall Recall through spreading activation — related memories surface naturally
nmem_health Brain health score (A–F) with actionable fix suggestions

Everything else — sessions, context loading, habit tracking, maintenance — works transparently in the background.

All 63 MCP tools →


What Makes This Different

Most memory tools are search engines. Neural Memory is a graph that thinks.

When you ask "Why did Tuesday's outage happen?", a vector database returns the most similar sentence. Neural Memory traces the chain:

outage ← CAUSED_BY ← JWT expiry ← SUGGESTED_BY ← Alice's review

Relationships are explicitCAUSED_BY, LEADS_TO, RESOLVED_BY, CONTRADICTS — so your agent doesn't just find memories, it reasons through them.

Search-based (RAG) Neural Memory
Retrieval Similarity score Graph traversal
Relationships None 24 explicit types
LLM required Yes (embedding) No — fully offline
Multi-hop reasoning Multiple queries One traversal
Memory lifecycle Static Decay, reinforcement, consolidation
Cost per 1K queries ~$0.02 $0.00

Cloud Sync — Your Data, Your Infrastructure

Sync your brain across every machine. Unlike other memory tools, we never store your data.

Laptop ←→ Your Cloudflare Worker ←→ Desktop
                  ↕
              Your Phone

You deploy the sync hub to your own Cloudflare account (free tier). Your D1 database, your encryption key, your data. We provide the code — you own the infrastructure.

nmem sync              # push/pull changes
nmem sync --auto       # auto-sync after every remember/recall

Sync uses Merkle delta — only diffs travel, not the full brain. Fast, efficient, private.

Cloud Sync setup guide →


Features

Memory & Recall

  • 14 memory types — fact, decision, error, insight, preference, workflow, instruction, and more
  • Spreading activation — memories surface by association, not keyword match
  • Cognitive reasoning — hypothesize, submit evidence, make predictions, verify with Bayesian confidence
  • Workload presetsnmem config preset {balanced,safe-cost,max-recall,chat-heavy} tune the brain for SaaS, frugal mode, deep retention, or conversational agents
  • Temporal recallnmem_causal exposes temporal_range and temporal_neighborhood actions; see the Temporal Recall Recipes guide

Knowledge Ingestion

  • Train from documents — PDF, DOCX, PPTX, HTML, JSON, XLSX, CSV ingested into permanent brain knowledge
  • Import adapters — migrate from ChromaDB, Mem0, Cognee, Graphiti, LlamaIndex in one command

Lifecycle & Storage

  • Memory consolidation — episodic memories mature into semantic knowledge over time
  • Compression tiers — full → summary → essence → ghost → metadata (reclaim storage, keep meaning)
  • Brain versioning — snapshot, rollback, diff, transplant memories between brains

Community

  • Brain Store — browse, import, and publish pre-built brains to the community marketplace
  • 3 seed brains — Python Best Practices, Git Workflows, Docker Essentials (ready to import)

Ecosystem

  • Web dashboard — 7-page React UI with graph visualization, health radar, timeline, mindmap, Brain Store
  • VS Code extension — memory tree, graph explorer, CodeLens, WebSocket sync (Marketplace →)
  • Safety — Fernet encryption, sensitive content auto-detection, parameterized SQL, path validation
  • Telegram backup — send brain .db files to Telegram for offsite backup

Quick Examples

# 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
nmem recall "auth bug"
nmem recall "database decision" --depth 2

# Brain management
nmem brain list && nmem brain health
nmem brain export -o backup.json

# Sync across devices
nmem sync --full

# Web dashboard
nmem serve    # http://localhost:8000/dashboard
import asyncio
from neural_memory import Brain
from neural_memory.storage import InMemoryStorage
from neural_memory.engine.encoder import MemoryEncoder
from neural_memory.engine.retrieval import ReflexPipeline

async def main():
    storage = InMemoryStorage()
    brain = Brain.create("my_brain")
    await storage.save_brain(brain)
    storage.set_brain(brain.id)

    encoder = MemoryEncoder(storage, brain.config)
    await encoder.encode("Met Alice to discuss API design")
    await encoder.encode("Decided to use FastAPI for backend")

    pipeline = ReflexPipeline(storage, brain.config)
    result = await pipeline.query("What did we decide about backend?")
    print(result.context)  # "Decided to use FastAPI for backend"

asyncio.run(main())

Neural Memory Pro

Free Neural Memory is complete — 63 tools, unlimited memories, fully offline. You never have to pay.

But past 10K memories, things change. Keyword matching misses semantically related content. Consolidation slows to minutes. Storage grows unbounded. If your agent's brain is getting big, Pro makes it smart.

Free recalls by keyword. Pro recalls by meaning.

Query: "authentication improvements"

Free (FTS5):  2 results — exact matches only
Pro  (HNSW):  7 results — includes "JWT rotation", "session hardening", "OAuth migration"

What Pro adds

Free (SQLite) Pro (InfinityDB)
Recall Keyword match (FTS5) Semantic similarity (HNSW)
Speed at 1M neurons ~500ms <5ms
Scale tested ~50K neurons 2M+ neurons
Compression Text-level trimming 5-tier vector compression (97% savings)
Consolidation O(N²) brute-force O(N×k) HNSW clustering
Storage per 1M ~5 GB ~1 GB
Cloud sync Manual push/pull Merkle delta (auto, diffs only)

Pro-exclusive features

  • Cone Queries — adjustable semantic recall. Narrow the cone for precision, widen for exploration
  • Smart Merge — consolidation that scales to 1M+ neurons using HNSW neighbor clustering
  • Directional Compression — compress along multiple semantic axes while preserving meaning
  • 5-Tier Auto Lifecycle — memories flow from float32 → float16 → int8 → binary → metadata. Auto-promote on access

Get Pro

pip install neural-memory                 # Pro features included
nmem shared activate --key NM-PRO-XXXX-XXXX-XXXX   # activate license
nmem shared status                                 # verify: Pro: Active

$9/mo — 30-day money-back guarantee. All free tools keep working. Downgrade anytime, keep your data.

Pro quickstart → · Full comparison → · Pricing →


Setup by Tool

<details> <summary><b>Claude Code (Plugin)</b></summary>

/plugin marketplace add nhadaututtheky/neural-memory
/plugin install neural-memory@neural-memory-marketplace

</details>

<details> <summary><b>Cursor / Windsurf / Other MCP Clients</b></summary>

pip install neural-memory

Add to your editor's MCP config:

{
  "mcpServers": {
    "neural-memory": { "command": "nmem-mcp" }
  }
}

</details>

<details> <summary><b>OpenClaw (Skill or Plugin)</b></summary>

Skill — one click via ClawHub. Published on every release:

clawhub.ai/skills/neural-memory

Plugin — memory slot replacement. Use this if you want NeuralMemory to be OpenClaw's memory provider rather than a skill it calls:

pip install neural-memory && npm install -g neuralmemory

Set memory slot in ~/.openclaw/openclaw.json:

{ "plugins": { "slots": { "memory": "neuralmemory" } } }

</details>

<details> <summary><b>Upgrade to Pro</b></summary>

Already using Neural Memory? Just activate your key:

nmem shared activate --key NM-PRO-XXXX-XXXX-XXXX   # activate license

Then enable InfinityDB (semantic search engine):

# ~/.neuralmemory/config.toml
storage_backend = "infinitydb"

Restart your MCP server. Existing memories are auto-migrated from SQLite to InfinityDB on first startup.

Get a license → · Pro quickstart →

</details>

<details> <summary><b>Installation extras</b></summary>

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[embeddings]          # Local embedding models
pip install neural-memory[embeddings-openai]   # OpenAI embeddings
pip install neural-memory[all]                 # Everything

</details>

<details> <summary><b>Benchmarks vs alternatives</b></summary>

Metric NeuralMemory Mem0 Cognee
Write 50 memories 1.2s 148.2s (121x slower) 290.6s (80x slower)
Read 20 queries 1.8s 2.9s 34.6s
API calls 0 70 149

Zero LLM calls, zero API cost. Full benchmarks → · Cognitive Efficiency release evidence →

</details>


Documentation

Guide Description
Quickstart Guide Interactive guide with animated demos
Pro Quickstart Get started with Pro features
CLI Reference All 82 CLI commands
MCP Tools Reference All 63 MCP tools with parameters
Cloud Sync Multi-device sync setup
Brain Health Guide Understanding and improving brain health
Embedding Setup Configure embedding providers
Architecture Technical design deep-dive

Development

git clone https://github.com/nhadaututtheky/neural-memory
cd neural-memory && pip install -e ".[dev]"
nmem doctor --dev        # Verify contributor setup
pytest tests/ -v          # 7800+ tests
ruff check src/ tests/    # Lint

See CONTRIBUTING.md for guidelines.

Support

If Neural Memory helps your AI agent remember, please consider giving it a star — it helps others discover the project and keeps development going.

<a href="https://github.com/nhadaututtheky/neural-memory/stargazers"> <img src="https://img.shields.io/github/stars/nhadaututtheky/neural-memory?style=social" alt="Star on GitHub"/> </a>

You can also sponsor the project.

License

MIT — see LICENSE.

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