Neural Memory

io.github.nhadaututtheky由 GitHub 账号 nhadaututtheky 发布v4.27.2更新于 Oct 24, 2026

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

发布方自己的服务:Memory.fit

已验证STDIO仅桌面知识与记忆AI 与机器学习

概览

AI 生成的概览

面向 AI 代理的本地持久记忆服务器:把记忆存成互联的神经元图,通过扩散激活召回,完全离线运行。

可以做什么
  • 存储记忆,自动识别类型、标签与关联
  • 通过扩散激活和图遍历召回相关记忆
  • 检查大脑健康度并给出修复建议
  • 把 PDF、DOCX、PPTX、HTML、JSON、XLSX、CSV 等文档导入为长期知识
  • 管理记忆生命周期:整合、压缩层级、快照、回滚与导出
  • 通过自建的 Cloudflare Worker 中枢在多台设备间同步大脑
适用场景
适合希望助手跨会话记住事实、决策、错误与偏好,又不想引入向量数据库或嵌入 API 调用的场景。也适合想要离线、基于显式关系图而非相似度检索进行推理的记忆工具的开发者。
运行要求
作为本地进程运行在用户机器上,从 PyPI 安装(pip install neural-memory),并在 MCP 客户端配置中用 nmem-mcp 命令启动。仅支持桌面端;未声明任何 API 密钥或环境变量。可选扩展包提供文档抽取、网页仪表盘、嵌入模型或云同步,Pro 功能需通过命令行激活许可证密钥。
安装前请注意
记忆会写入本地数据库并在会话之间保留,存入的内容会留在磁盘上;虽提供敏感内容自动检测与 Fernet 加密,但不宜单独依赖。可选的云同步需要在你自己的 Cloudflare 账户中部署中枢,并使用你自己的数据库和加密密钥。Telegram 备份会把大脑数据库文件发送到 Telegram。Pro 为付费订阅,需用许可证密钥激活。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Neural Memory,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

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.

来源:README.md,提交 2015cb9

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

1
  1. v4.27.2最新Sep 16, 2026

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其他 Memory 集成