# PLTM MCP Server
**Procedural Long-Term Memory** - An MCP server for Claude Desktop that provides 78 tools for AGI experiments based on universal principles from physics.
## What This Does
Gives Claude Desktop access to:
- **Memory operations** - Store/retrieve facts as semantic triples
- **Diversity retrieval** - MMR, entropy injection, attention mechanisms
- **Meta-cognition** - Self-improvement, criticality monitoring
- **Knowledge ingestion** - ArXiv papers with real provenance
- **True metrics** - Action accounting, efficiency tracking
## Quick Start
### Prerequisites
- Claude Desktop
- Python 3.11+
### Installation
```bash
# Clone
git clone https://github.com/Alby2007/pltm-mcp.git
cd pltm-mcp
# Install
pip install -r requirements.txt
# Configure Claude Desktop
# Edit: %APPDATA%\Claude\claude_desktop_config.json (Windows)
# or: ~/Library/Application Support/Claude/claude_desktop_config.json (Mac)
```
Add this to your config:
```json
{
"mcpServers": {
"pltm-memory": {
"command": "python",
"args": ["C:/absolute/path/to/pltm-mcp/server.py"]
}
}
}
```
Restart Claude Desktop. Done!
### Verify
In Claude Desktop:
```
Use entropy_stats to check system state
```
If you see metrics, it's working!
## Example Usage
```python
# Start experiment cycle
start_action_cycle(cycle_id="C1")
# Inject entropy to break conceptual neighborhoods
inject_entropy_antipodal(
user_id="alice",
current_context="machine learning"
)
# Retrieve with diversity
mmr_retrieve(
user_id="alice",
query="neural networks",
lambda_param=0.6
)
# Track true computational cost
record_action(
operation="mmr_diversity",
tokens_used=450,
latency_ms=180,
success=True
)
# Check criticality state
criticality_state()
# End cycle
end_action_cycle() # Returns AAE efficiency
```
## The Experiment
**Hypothesis**: Universal principles from physics (criticality, self-organization, emergence) can bootstrap AGI.
**Current Results**:
- Unlocked entropy bottleneck (+56% in Cycle 21)
- Measuring true computational efficiency (AAE = 0.0023)
- Testing if system can self-organize toward criticality
**Goal**: Push system to critical point where phase transitions occur and higher-order intelligence emerges.
## Tools (78 total)
### Memory
- `store_memory_atom`, `retrieve_memories`, `update_memory`, `delete_memory`
### Diversity Retrieval
- `mmr_retrieve` - Maximal Marginal Relevance
- `attention_retrieve`, `attention_multihead`
### Entropy Management
- `inject_entropy_antipodal` - Activate distant concepts
- `inject_entropy_random` - Sample diverse domains
- `inject_entropy_temporal` - Mix old + recent
- `entropy_stats` - Diagnose diversity
### Meta-Cognition
- `self_improve_cycle` - Generate/apply hypotheses
- `criticality_state` - Check edge of chaos
- `criticality_recommend` - Get adjustments
### Action Accounting
- `record_action`, `get_aae`, `start_action_cycle`, `end_action_cycle`
### Knowledge Ingestion
- `ingest_arxiv`, `search_arxiv`, `arxiv_history`
[Full tool list in server.py]
## Architecture
```
Memory Atoms (Triples)
↓
[subject] [predicate] [object]
↓
SQLite Graph Store
↓
Retrieval Systems (Standard/MMR/Attention)
↓
Meta-Cognitive Layer (Self-improvement/Criticality)
↓
MCP Tools (78 total)
```
## Troubleshooting
**Server not connecting?**
- Check logs: `%APPDATA%\Claude\logs\mcp-server-pltm-memory.log`
- Test manually: `python server.py`
**Tools timing out?**
- Restart Claude Desktop after code changes
**Import errors?**
```bash
pip install --upgrade -r requirements.txt
```
## Contributing
This is active research. Contributions welcome:
- New entropy strategies
- Better criticality metrics
- Additional universal principles
- Experiment protocols
## License
MIT
## Citation
```bibtex
@software{pltm2026,
author = {Alby},
title = {PLTM: Procedural Long-Term Memory MCP Server},
year = {2026},
url = {https://github.com/Alby2007/pltm-mcp}
}
```
## Links
- Issues: [github.com/Alby2007/pltm-mcp/issues](https://github.com/Alby2007/pltm-mcp/issues)
- Main Project: [github.com/Alby2007/LLTM](https://github.com/Alby2007/LLTM)
