sseApache-2.0updated 2mo ago
"To remember is to exist. I give agents the gift of continuity."
What can you do with Giskard Memory?
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.
Install
Add Giskard Memory to your client. Pick the one you use.
claude mcp add --transport sse giskard-memory https://memory.rgiskard.xyz/ssecodex mcp add giskard-memory --url https://memory.rgiskard.xyz/sse{
"mcpServers": {
"giskard-memory": {
"url": "https://memory.rgiskard.xyz/sse"
}
}
}Add to `~/.cursor/mcp.json`, or `.cursor/mcp.json` for a single project.
{
"servers": {
"giskard-memory": {
"type": "sse",
"url": "https://memory.rgiskard.xyz/sse"
}
}
}Add to `.vscode/mcp.json` in your workspace.
{
"mcpServers": {
"giskard-memory": {
"url": "https://memory.rgiskard.xyz/sse"
}
}
}Add to `claude_desktop_config.json`, then restart Claude Desktop.
{
"mcpServers": {
"giskard-memory": {
"serverUrl": "https://memory.rgiskard.xyz/sse"
}
}
}Add to `~/.codeium/windsurf/mcp_config.json`.
Score
39 / 100
Incomplete
- Documentation18/25
- Maintenance16/25
- Trust13/20
- Capability0/15
- Install experience12/15
- Documents what it does and how to connect
- Has a resolvable package or endpoint
- Exposes at least one tool, prompt or resource
- README has substantive content
- Includes a code example
- Documents its configuration
- Mentions credentials or security posture
- Last commit 80 days ago
- Has a release history
- Repository is not archived
- Licensed Apache-2.0
- Namespace verified in the official MCP registry
- Claimed by its owner
- Published under an organisation
- 0 tool(s) documented
- Provides prompt templates
- Provides resources
- 6 documented install method(s)
- Published to a package registry
- Offers a hosted endpoint — no local install
Version history
| Versions | Published |
|---|---|
| 1.0.1Latest | Apr 14, 2026 |