io.github.nhadaututtheky/neural-memory MCP Server
io.github.nhadaututtheky/neural-memory
Persistent memory for AI agents using spreading activation — no vector DB, no API calls, fully offline.
What is the io.github.nhadaututtheky/neural-memory MCP server?
The Neural Memory MCP server gives AI agents persistent memory across sessions using a graph-based architecture with spreading activation recall, similar to how the human brain works. It stores memories as interconnected neurons and retrieves them through relationship traversal rather than keyword matching, with 63 MCP tools available but only 3 core tools needed for most use cases.
Neural Memory solves the problem of AI agents forgetting everything between sessions. Instead of traditional vector databases, it uses a graph structure with explicit relationships (CAUSED_BY, LEADS_TO, RESOLVED_BY, etc.) to store and recall memories. The system works fully offline with no embedding costs, supports multi-device sync via your own Cloudflare infrastructure, and includes features like memory consolidation, compression tiers, and brain versioning. Free tier handles up to ~50K memories; Pro tier adds semantic search and scales to 2M+ neurons.
How to install io.github.nhadaututtheky/neural-memory
Copy-paste configuration for popular MCP clients.
Tools & capabilities
Tools this server exposes to the agent.
nmem_remember— Store a memory with auto-detected type, tags, and connections to existing memoriesnmem_recall— Recall memories through spreading activation — related memories surface naturally via graph traversalnmem_health— Brain health score (A–F) with actionable fix suggestionsnmem_causal— Temporal recall with temporal_range and temporal_neighborhood actions for time-based memory explorationnmem_config— Configure workload presets (balanced, safe-cost, max-recall, chat-heavy) to tune brain behaviornmem_brain— Brain management tools including list, health check, export, snapshot, rollback, and diff operationsnmem_sync— Cloud sync across devices using Merkle delta — push/pull changes or enable auto-syncnmem_serve— Launch web dashboard (React UI) with graph visualization, health radar, timeline, and mindmapnmem_train— Ingest documents (PDF, DOCX, PPTX, HTML, JSON, XLSX, CSV) into permanent brain knowledgenmem_import— Migrate memories from ChromaDB, Mem0, Cognee, Graphiti, or LlamaIndex
Use cases
- Store and recall project decisions, bugs, and solutions with automatic relationship detection across sessions
- Build AI agents that reason through multi-hop memory chains (e.g., trace an outage back to its root cause through explicit relationships)
- Maintain a persistent knowledge base of workflows, instructions, and best practices that grows smarter over time
- Sync agent memory across multiple devices using your own Cloudflare infrastructure with zero data exposure to third parties
- Track temporal patterns and causal relationships in memories to enable time-aware and evidence-based reasoning
io.github.nhadaututtheky/neural-memory MCP server FAQ
Neural Memory is a graph-based memory system that stores memories as interconnected neurons with explicit relationship types (24 types like CAUSED_BY, LEADS_TO, RESOLVED_BY). It recalls memories through spreading activation and graph traversal rather than similarity scoring. It requires no vector embeddings, no API calls, and works fully offline — making it faster and free to operate at scale.
Yes. The free tier is complete with 63 MCP tools, unlimited memories, full offline operation, and supports up to ~50K neurons. Pro ($9/mo) adds semantic search via HNSW, scales to 2M+ neurons, includes cone queries and smart merge consolidation, and enables auto cloud sync. Free features never expire or degrade.
For Cursor/Windsurf: run `pip install neural-memory`, then add to your MCP config: `{"mcpServers": {"neural-memory": {"command": "nmem-mcp"}}}`. For Claude Code, use `/plugin marketplace add nhadaututtheky/neural-memory`. For OpenClaw, install via ClawHub at clawhub.ai/skills/neural-memory or as a plugin.
No. Neural Memory is fully offline and requires no API keys, authentication, or external services. Optional: Pro features use a local license key. Optional: Cloud Sync uses your own Cloudflare account (free tier) — you own the infrastructure and encryption key.
Cloud Sync uses Merkle delta to sync only diffs between devices via your own Cloudflare Worker and D1 database. Neural Memory never stores your data — you deploy the sync hub to your Cloudflare account and control the encryption key. Sync is optional; local-only operation is fully supported.
14 memory types: fact, decision, error, insight, preference, workflow, instruction, and more. Type is auto-detected when you store a memory, but can be explicitly set. Memories mature through consolidation (episodic → semantic) and compress through tiers (full → summary → essence → ghost → metadata) to reclaim storage while preserving meaning.
README (reference)
Source of truth, from the repository.
NeuralMemory
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 longerneural-memory). There is nonmbinary.
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.
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 | |
|---|---|---|
| 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.
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_causalexposestemporal_rangeandtemporal_neighborhoodactions; 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
.dbfiles 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.
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.
</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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