pkg-memory-bridge
Bridge to PKG systems (Mem0, Graphiti, Solid PODs, Logseq) for individuated information indices
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install plurigrid-asi-pkg-memory-bridge
Repository
Skill path: skills/pkg-memory-bridge
Bridge to PKG systems (Mem0, Graphiti, Solid PODs, Logseq) for individuated information indices
Open repositoryBest for
Primary workflow: Ship Full Stack.
Technical facets: Full Stack.
Target audience: everyone.
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: plurigrid.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install pkg-memory-bridge into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/plurigrid/asi before adding pkg-memory-bridge to shared team environments
- Use pkg-memory-bridge for development workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.
Original source / Raw SKILL.md
---
name: pkg-memory-bridge
description: Bridge to PKG systems (Mem0, Graphiti, Solid PODs, Logseq) for individuated information indices
version: 1.0.0
---
# PKG Memory Bridge Skill
Connects music-topos to external Personal Knowledge Graph systems.
## GF(3) Triads
```
shadow-goblin (-1) ⊗ pkg-memory-bridge (0) ⊗ gay-mcp (+1) = 0 ✓ [Memory Trace]
temporal-coalgebra (-1) ⊗ pkg-memory-bridge (0) ⊗ agent-o-rama (+1) = 0 ✓ [Temporal KG]
keychain-secure (-1) ⊗ pkg-memory-bridge (0) ⊗ pulse-mcp-stream (+1) = 0 ✓ [Auth + Stream]
```
## Supported Systems
| System | API | Use Case |
|--------|-----|----------|
| Mem0 | `pip install mem0ai` | LLM agent memory |
| Graphiti | MCP Server | Temporal knowledge graph |
| Solid POD | REST/SPARQL | Decentralized personal data |
| Logseq | Local DB | Block-level PKB |
## Quick Integration
```python
from mem0 import Memory
m = Memory()
m.add("User prefers GF(3) balanced triads", user_id="bmorphism")
results = m.search("color conservation", user_id="bmorphism")
```
## Graphiti MCP
```bash
# Add to .mcp.json
{"mcpServers": {"graphiti": {"command": "uvx", "args": ["graphiti-mcp"]}}}
```
## Key Researchers
- Krisztian Balog (PKG ecosystem)
- Gordon Bell (MyLifeBits/memex)
- Mem0 team (Prateek Chhikara, Taranjeet Singh)
- Zep/Graphiti (temporal KG)
## Scientific Skill Interleaving
This skill connects to the K-Dense-AI/claude-scientific-skills ecosystem:
### Graph Theory
- **networkx** [○] via bicomodule
- Universal graph hub
### Bibliography References
- `general`: 734 citations in bib.duckdb
## Cat# Integration
This skill maps to **Cat# = Comod(P)** as a bicomodule in the equipment structure:
```
Trit: 0 (ERGODIC)
Home: Prof
Poly Op: ⊗
Kan Role: Adj
Color: #26D826
```
### GF(3) Naturality
The skill participates in triads satisfying:
```
(-1) + (0) + (+1) ≡ 0 (mod 3)
```
This ensures compositional coherence in the Cat# equipment structure.