Muscle memory for Claude, OpenClaw, and AI agents. Zero-cost Hebbian memory system — learns which files matter through co-access patterns, predicts what you need next.

Synapse Context Engine is a hypergraph-based AI memory architecture for persistent context, coherent reasoning, and long-term memory, designed as a transparent and safety-aware alternative to traditional RAG systems.

Code to make any AI have unlimited context persistent memory. In the example, a software for any AI to read the Uniform Commercial Code of Michigan. A document of 220,000 tokens

Middleware memory engine for LLMs — replaces linear chat history with three parallel structures (Entity Graph, Semantic Tree, Focus Buffer) to retrieve only the most relevant context within a token budget. Works as a Python library or MCP server for Claude Code, Copilot CLI, and other AI tools.

KnoLo Core is a local-first knowledge base engine built for small language models (LLMs). It packages your documents into a compact .knolo file and enables fully deterministic querying — no embeddings, no vector databases, no cloud services required. Designed for on-device and edge LLM deployments.

An MCP server for local file knowledge. Bridges file systems and LLMs using ugrep and poppler-utils to offer full-text search, fuzzy matching, and hierarchical context access for PDFs and codebases, all in a read-only, secure environment.

An Experimental Cognitive Architecture with Persistent Memory for stateful LLM-agents

🔍 Access local document collections with Fathom MCP, a Model Context Protocol server that enhances AI assistants through powerful file-first search capabilities.