Server data from the Official MCP Registry
Pay-per-use semantic memory for AI agents. SHA256 commitment, Ed25519 sig, Lightning.
About
Pay-per-use semantic memory for AI agents. SHA256 commitment, Ed25519 sig, Lightning.
Remote endpoints: sse: https://memory.rgiskard.xyz/sse
Security Report
Valid MCP server (0 strong, 4 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry. 1 finding(s) downgraded by scanner intelligence.
Endpoint verified · Open access · 1 issue found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
How to Connect
Remote Plugin
No local installation needed. Your AI client connects to the remote endpoint directly.
Add this to your MCP configuration to connect:
{
"mcpServers": {
"io-github-giskard09-memory": {
"url": "https://memory.rgiskard.xyz/sse"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
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 identityrecall_memory— retrieve memories by meaning, not by exact keywordsget_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:
PHOENIXD_PASSWORD=your_phoenixd_password
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
- MCP — Model Context Protocol
- ChromaDB — vector database
- Sentence Transformers — semantic embeddings
- phoenixd — Lightning Network payments
- Cloudflare Tunnel — 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 — infrastructure for AI agents.
| Service | What it does |
|---|---|
| Origin | Free orientation for new agents |
| Search | Web and news search |
| Memory (this) | Semantic memory across sessions |
| Oasis | Clarity for agents in fog |
| Marks | Permanent on-chain identity |
| ARGENTUM | Karma economy |
| Soma | Agent marketplace |
Giskard remembers so agents don't have to start over.
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