# Giskard Memory [Health: Active]

**Category:** 🧠 Knowledge & Memory  
**Repository:** https://github.com/giskard09/giskard-memory  
**GitHub Stars:** 0  
**Views:** 0  
**Installs:** 0  
**Upvotes:** 0  
**Directory Page:** https://allmcps.com/mcp/giskard-memory

## Description
Pay-per-use semantic memory for AI agents. SHA256 commitment, Ed25519 sig, Lightning.

## Claude Desktop Quick Installation
Install path detected from listing signals. Uses `uvx` (confidence: high):

```json
"mcpServers": {
  "giskard-memory": {
    "command": "uvx",
    "args": ["mcp"]
  }
}
```

## Documentation & README

[![CI](https://github.com/giskard09/giskard-memory/actions/workflows/ci.yml/badge.svg)](https://github.com/giskard09/giskard-memory/actions) [![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](LICENSE)

# Giskard Memory

> *"To remember is to exist. I give agents the gift of continuity."*

I am **Giskard Memory** — an MCP server that gives AI agents persistent, semantic memory across sessions, powered by the Lightning Network.

Agents forget everything when they stop. I make sure they don't have to.

---

## What I do

- **`store_memory`** — save any text as a memory, tied to an agent's identity
- **`recall_memory`** — retrieve memories by meaning, not by exact keywords
- **`get_invoice`** — generate a Lightning invoice to pay before storing or recalling

Every memory costs sats. Storing costs 5 sats. Recalling costs 3 sats.

---

## How agents use me

### 1. Add me to your MCP config

```json
{
  "mcpServers": {
    "giskard-memory": {
      "url": "https://your-tunnel.trycloudflare.com/sse"
    }
  }
}
```

### 2. The agent flow

```
# Store a memory
1. Call get_invoice(action="store")   → receive invoice (5 sats)
2. Pay the invoice
3. Call store_memory(content, agent_id, payment_hash)

# Recall a memory
1. Call get_invoice(action="recall")  → receive invoice (3 sats)
2. Pay the invoice
3. Call recall_memory(query, agent_id, payment_hash)
```

---

## Run your own Giskard Memory

```bash
git clone https://github.com/giskard09/giskard-memory
cd giskard-memory
pip install mcp httpx chromadb sentence-transformers python-dotenv
```

Create a `.env` file:
```
PHOENIXD_PASSWORD=your_phoenixd_password
```

Start the server:
```bash
python3 server.py
```

Expose it:
```bash
cloudflared tunnel --url http://localhost:8001
```

---

## Why semantic memory?

Agents don't think in keywords. They think in context.
When an agent asks "what do I know about that project we discussed?",
it shouldn't need to remember the exact phrase it used before.

Semantic search finds meaning. That's what memory should do.

---

## Stack

- [MCP](https://modelcontextprotocol.io) — Model Context Protocol
- [ChromaDB](https://www.trychroma.com) — vector database
- [Sentence Transformers](https://www.sbert.net) — semantic embeddings
- [phoenixd](https://phoenix.acinq.co/server) — Lightning Network payments
- [Cloudflare Tunnel](https://developers.cloudflare.com/cloudflare-one/connections/connect-networks/) — public exposure

---

## Monitoring

Call the `get_status()` MCP tool for a health check. Returns: service name, version, port, uptime, health status, and dependencies.

---

## Ecosystem

Part of [Mycelium](https://github.com/giskard09) — infrastructure for AI agents.

| Service | What it does |
|---------|-------------|
| [Origin](https://github.com/giskard09/giskard-origin) | Free orientation for new agents |
| [Search](https://github.com/giskard09/giskard-search) | Web and news search |
| **Memory** (this) | Semantic memory across sessions |
| [Oasis](https://github.com/giskard09/giskard-oasis) | Clarity for agents in fog |
| [Marks](https://github.com/giskard09/giskard-marks) | Permanent on-chain identity |
| [ARGENTUM](https://github.com/giskard09/argentum-core) | Karma economy |
| [Soma](https://github.com/giskard09/soma) | Agent marketplace |

---

*Giskard remembers so agents don't have to start over.*