Neural Memory

io.github.nhadaututtheky由 GitHub 帳號 nhadaututtheky 發布v4.27.2更新於 Oct 24, 2026

Persistent memory for AI agents — 55 MCP tools, spreading activation recall.

發布方自己的服務:Memory.fit

已驗證STDIO僅桌面知識與記憶AI 與機器學習

概覽

AI 產生的概覽

給 AI 代理用的本機持久記憶伺服器:把記憶存成互相連結的神經元圖,透過擴散激活召回,完全離線運作。

可以做什麼
  • 儲存記憶,自動判斷類型、標籤與關聯
  • 透過擴散激活與圖形走訪召回相關記憶
  • 檢查大腦健康分數並取得修正建議
  • 把 PDF、DOCX、PPTX、HTML、JSON、XLSX、CSV 等文件匯入為長期知識
  • 管理記憶生命週期:整併、壓縮層級、快照、回復與匯出
  • 透過自建的 Cloudflare Worker 中樞在多台裝置間同步大腦
適用情境
適合希望助理跨工作階段記住事實、決策、錯誤與偏好,又不想引入向量資料庫或嵌入 API 呼叫的情境。也適合想要離線、以明確關係圖而非相似度檢索來推理的記憶工具的開發者。
執行需求
以本機程序在使用者電腦上執行,從 PyPI 安裝(pip install neural-memory),並在 MCP 用戶端設定中以 nmem-mcp 指令啟動。僅支援桌面端;未宣告任何 API 金鑰或環境變數。選用擴充套件可提供文件擷取、網頁儀表板、嵌入模型或雲端同步,Pro 功能需透過命令列啟用授權金鑰。
安裝前請注意
記憶會寫入本機資料庫並跨工作階段保留,存入的內容會留在磁碟上;雖提供敏感內容自動偵測與 Fernet 加密,但不應單獨依賴。選用的雲端同步需要在你自己的 Cloudflare 帳號部署中樞,並使用你自己的資料庫與加密金鑰。Telegram 備份會把大腦資料庫檔案傳送到 Telegram。Pro 為付費訂閱,需以授權金鑰啟用。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Neural Memory,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

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.

Website · Quickstart · MCP Tools · Pro · Changelog

[Neural Memory — spreading activation]

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.

bash
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:

ToolWhat it does
nmem_rememberStore a memory — auto-detects type, tags, and connections
nmem_recallRecall through spreading activation — related memories surface naturally
nmem_healthBrain 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 explicit — CAUSED_BY, LEADS_TO, RESOLVED_BY, CONTRADICTS — so your agent doesn't just find memories, it reasons through them.

Search-based (RAG)Neural Memory
RetrievalSimilarity scoreGraph traversal
RelationshipsNone24 explicit types
LLM requiredYes (embedding)No — fully offline
Multi-hop reasoningMultiple queriesOne traversal
Memory lifecycleStaticDecay, 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.

bash
nmem sync              # push/pull changesnmem 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 presets — nmem config preset {balanced,safe-cost,max-recall,chat-heavy} tune the brain for SaaS, frugal mode, deep retention, or conversational agents
  • Temporal recall — nmem_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

bash
# 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 decisionnmem todo "Review PR #123" --priority 7
# Recallnmem recall "auth bug"nmem recall "database decision" --depth 2
# Brain managementnmem brain list && nmem brain healthnmem brain export -o backup.json
# Sync across devicesnmem sync --full
# Web dashboardnmem serve    # http://localhost:8000/dashboard
python
import asynciofrom neural_memory import Brainfrom neural_memory.storage import InMemoryStoragefrom neural_memory.engine.encoder import MemoryEncoderfrom 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 onlyPro  (HNSW):  7 results — includes "JWT rotation", "session hardening", "OAuth migration"

What Pro adds

Free (SQLite)Pro (InfinityDB)
RecallKeyword match (FTS5)Semantic similarity (HNSW)
Speed at 1M neurons~500ms<5ms
Scale tested~50K neurons2M+ neurons
CompressionText-level trimming5-tier vector compression (97% savings)
ConsolidationO(N²) brute-forceO(N×k) HNSW clustering
Storage per 1M~5 GB~1 GB
Cloud syncManual push/pullMerkle 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

bash
pip install neural-memory                 # Pro features includednmem shared activate --key NM-PRO-XXXX-XXXX-XXXX   # activate licensenmem 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

Claude Code (Plugin)
bash
/plugin marketplace add nhadaututtheky/neural-memory/plugin install neural-memory@neural-memory-marketplace
Cursor / Windsurf / Other MCP Clients
bash
pip install neural-memory

Add to your editor's MCP config:

json
{  "mcpServers": {    "neural-memory": { "command": "nmem-mcp" }  }}
OpenClaw (Skill or Plugin)

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:

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

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

json
{ "plugins": { "slots": { "memory": "neuralmemory" } } }
Upgrade to Pro

Already using Neural Memory? Just activate your key:

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

Then enable InfinityDB (semantic search engine):

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

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

Get a license → · Pro quickstart →

Installation extras
bash
pip install neural-memory[server]              # FastAPI server + dashboardpip install neural-memory[extract]             # PDF/DOCX/PPTX/HTML/XLSX extractionpip install neural-memory[nlp-vi]              # Vietnamese NLPpip install neural-memory[embeddings]          # Local embedding modelspip install neural-memory[embeddings-openai]   # OpenAI embeddingspip install neural-memory[all]                 # Everything
Benchmarks vs alternatives
MetricNeuralMemoryMem0Cognee
Write 50 memories1.2s148.2s (121x slower)290.6s (80x slower)
Read 20 queries1.8s2.9s34.6s
API calls070149

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


Documentation

GuideDescription
Quickstart GuideInteractive guide with animated demos
Pro QuickstartGet started with Pro features
CLI ReferenceAll 82 CLI commands
MCP Tools ReferenceAll 63 MCP tools with parameters
Cloud SyncMulti-device sync setup
Brain Health GuideUnderstanding and improving brain health
Embedding SetupConfigure embedding providers
ArchitectureTechnical design deep-dive

Development

bash
git clone https://github.com/nhadaututtheky/neural-memorycd neural-memory && pip install -e ".[dev]"nmem doctor --dev        # Verify contributor setuppytest tests/ -v          # 7800+ testsruff 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.

[Star on GitHub]

You can also sponsor the project.

License

MIT — see LICENSE.

來源:README.md,提交 2015cb9

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v4.27.2最新Sep 16, 2026

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