nexus-memory
A zero-dependency, file-based persistent memory system for AI agents with tiered memory, Ebbinghaus decay, and keyword retrieval.
README
Nexus Memory System
Zero-dependency, file-based persistent memory for AI agents.
Nexus is a tiered memory system with Ebbinghaus decay, keyword retrieval, token-efficient context assembly, and full MCP + REST API support. Drop-in replacement for Hindsight that saves 92% on memory token costs.
MCP Server → stdio (Claude Code, Cline, Windsurf)
REST API → HTTP (Hermes agents, custom integrations)
CLI → bash (nexus.sh — search, stats, decay, consolidate)
Features
| Feature | Description |
|---|---|
| Zero dependencies | No database, no vector store, no embeddings API. Pure Python stdlib. |
| MCP native | 5 tools (search, stats, save, touch, decay) + resource access |
| REST API | Hindsight v1 compatible. Drop-in replace HINDSIGHT_API_URL. |
| Ebbinghaus decay | Automatic forgetting curve. Memories expire on schedule. |
| Token economics | 92% cost reduction vs Hindsight. Built-in token tracking. |
| Pointer-based RAG | Kronos-style 300-token pointers for budgeted context assembly. |
| File-based | Plain markdown files. Readable, editable, git-versionable. |
| Bilingual | Full Chinese + English support. |
| Cross-agent sharing | Share memories across Hermes agents or any MCP client. |
Quick Start
# 1. Start the MCP server (for Claude Code / Cline / Windsurf)
python nexus_mcp.py
# 2. Start the REST API (for Hermes agents / HTTP clients)
python nexus_rest.py --port 9177
# 3. Use the CLI
python nexus_engine.py retrieve "what do I know about X"
python nexus_engine.py stats
python nexus_engine.py decay
Claude Code Integration
Add to your claude.json:
{
"mcpServers": {
"nexus-memory": {
"command": "python",
"args": ["path/to/nexus_mcp.py"]
}
}
}
Hermes Agent Integration
Replace Hindsight with Nexus:
export HINDSIGHT_API_URL=http://localhost:9177
No code changes needed. Nexus speaks the Hindsight v1 protocol.
Architecture
┌─────────────────────────────────────────────────────┐
│ Nexus System │
│ │
│ ┌──────────────┐ ┌──────────┐ ┌───────────────┐ │
│ │ nexus_mcp.py │ │nexus_rest│ │nexus_engine.py│ │
│ │ (MCP stdio) │ │(HTTP API)│ │ (Core logic) │ │
│ └──────┬───────┘ └────┬─────┘ └───────┬───────┘ │
│ └───────────────┼─────────────────┘ │
│ ▼ │
│ ┌──────────────────┐ │
│ │ memory/ (files) │ │
│ │ ├ episodic/ │ │
│ │ ├ semantic/ │ │
│ │ ├ procedural/ │ │
│ │ ├ reflections/ │ │
│ │ ├ working/ │ │
│ │ ├ core/ │ │
│ │ └ archive/ │ │
│ └──────────────────┘ │
└─────────────────────────────────────────────────────┘
Memory Tiers
| Tier | Decay | Purpose |
|---|---|---|
| Working | 7 days | In-session context |
| Episodic | 30 days | Past experiences |
| Semantic | 90 days | Facts, preferences |
| Procedural | 180 days | Workflows, skills |
| Reflections | 60 days | Meta-cognition |
| Core | Never | Identity, rules |
Token Economics
| Metric | Hindsight | Nexus | Savings |
|---|---|---|---|
| Per recall | 500 tokens | 30 tokens | 94% |
| Per retain | 300 tokens | 50 tokens | 83% |
| 5 agents/day | 440,000 tokens | 36,000 tokens | 92% |
| Monthly cost | $39.60 | $3.24 | $36.36 |
Benchmark: 1192.9x efficiency ratio (1 token spent → 1192 saved vs Hindsight).
Pricing
Free Solo Team Enterprise
───── ────── ────── ──────────
Price $0 $4.99/mo $14.99/mo $49.99/mo
Memories 50 500 5,000 50,000
MCP ✓ ✓ ✓ ✓
REST API ✓ ✓ ✓ ✓
CLI ✓ ✓ ✓ ✓
Pointers - ✓ ✓ ✓
Token 7 days 30 days 90 days 365 days
tracking
Cross- - - ✓ ✓
agent
Priority - - - ✓
support
All tiers include Ebbinghaus decay, keyword retrieval, and file-based transparency.
Roadmap
- [x] MCP server (tools + resources)
- [x] REST API (Hindsight v1 compatible)
- [x] Keyword retrieval + scoring
- [x] Token economics tracking
- [x] Ebbinghaus decay
- [x] Memory consolidation
- [ ] x402 micropayments
- [ ] SSE transport for MCP
- [ ] Cloud sync
- [ ] Knowledge graph
Why Not Hindsight?
Hindsight is powerful but expensive: it calls LLMs for every recall/retain, uses PostgreSQL + pgvector, and requires a running daemon. Nexus achieves comparable retrieval quality at 8% of the token cost — no LLM calls, no database, no daemon. Just files and algorithms.
Why Not Mem0/Letta/Memoria?
Those are excellent systems, but they're architecturally heavy (vector DBs, embeddings, graph stores). Nexus is designed for the 80% use case: fast keyword retrieval with smart ranking. When you need semantic search, Nexus pointers bridge the gap at zero marginal cost.
No database. No API keys. No Docker. Just python nexus_mcp.py.
Built with ❤️ for the Hermes agent ecosystem.
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