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Giskard Memory MCP Server

Developer ToolsLow Risk9.9MCP RegistryRemote
Free

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

9.9
Low Risk9.9Low Risk

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.

file_system

Check that this permission is expected for this type of plugin.

HTTP Network Access

Connects to external APIs or services over the internet.

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 GitHub

From the project's GitHub README.

CI 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

{
  "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


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.

ServiceWhat it does
OriginFree orientation for new agents
SearchWeb and news search
Memory (this)Semantic memory across sessions
OasisClarity for agents in fog
MarksPermanent on-chain identity
ARGENTUMKarma economy
SomaAgent marketplace

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

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