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PLTM

Alby2007byAlby2007
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Data Science & ML

Extends Claude Desktop with advanced memory, meta-cognition, and knowledge ingestion tools for AGI research.

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PLTM is an MCP server designed to augment Claude Desktop with a comprehensive suite of 78 tools, enabling sophisticated AGI experiments. It empowers Claude with capabilities such as storing and retrieving facts as semantic triples, diverse information retrieval mechanisms like MMR and attention, and meta-cognitive functions including self-improvement and criticality monitoring. Furthermore, it facilitates knowledge ingestion from sources like ArXiv and tracks true computational efficiency through action accounting. The project operates under the hypothesis that universal principles from physics, such as criticality and self-organization, can bootstrap AGI, aiming to push the system towards a critical point where higher-order intelligence may emerge.

Key Features

01Advanced Memory Operations (Semantic Triples)
02Knowledge Ingestion from ArXiv
03Diverse Retrieval Mechanisms (MMR, Attention, Entropy Injection)
04Computational Efficiency Tracking (Action Accounting)
05Meta-Cognitive Functions (Self-Improvement, Criticality Monitoring)
062 GitHub stars

Use Cases

01Conducting AGI experiments leveraging physics principles for system behavior
02Enhancing Claude Desktop with sophisticated long-term memory and learning capabilities
03Researching and optimizing AI self-organization and emergent intelligence