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giskard-memory

Pay-per-use semantic memory for AI agents with cryptographic attestation. Vector embeddings with SHA256 commitment, secp256k1 signature, and Lightning invoice.

glama
Updated
Apr 3, 2026

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

{
  "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

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

Create a .env file:

ALBY_API_KEY=your_alby_api_key

Start the server:

python3 server.py

Expose it:

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


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

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