Pltm MCP

🚀 PLTM MCP Server

Procedural Long-Term Memory - An MCP server for Claude Desktop that offers 78 tools for AGI experiments based on universal principles from physics.

🚀 Quick Start

Prerequisites

• Claude Desktop
• Python 3.11+

Installation

# 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:

{
  "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!

✨ Features

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

💻 Usage Examples

Basic Usage

# 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

📚 Documentation

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?

pip install --upgrade -r requirements.txt

🔧 Technical Details

The PLTM MCP Server is structured to provide Claude Desktop with a wide - range of capabilities for AGI experiments. It starts with storing memory atoms as semantic triples in an SQLite graph store. The retrieval systems are designed to offer both standard and more advanced diversity - based retrieval methods such as MMR and attention mechanisms. The meta - cognitive layer allows the system to self - improve and monitor its criticality state. The 78 MCP tools are divided into several categories including memory operations, diversity retrieval, entropy management, meta - cognition, action accounting, and knowledge ingestion. These components work together to test the hypothesis that universal principles from physics can bootstrap AGI.

🤝 Contributing

This is active research. Contributions welcome:

• New entropy strategies
• Better criticality metrics
• Additional universal principles
• Experiment protocols

📄 License

MIT

📚 Citation

@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
• Main Project: github.com/Alby2007/LLTM