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    Self-improving, verifiable memory for AI coding agents. Learns how you work, stops repeating mistakes, models each project, recalls the right lesson at the right moment. Every memory is signed and tamper-evident. Local-first.
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    Apache 2.0
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    Semantic memory for AI builders: capture the tacit engineering know-how that never reaches your docs, recall it the moment it applies. Built in Rust on Postgres and pgvector.
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    Serves portable behavioral identity models via MCP. Extracts how a person thinks, communicates, and makes decisions from text, then provides always-on identity context, semantic fact retrieval, keyword search, and provenance tracing through 4 tools and 1 resource.
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    Apache 2.0
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    Local-first semantic memory server with project indexing for AI assistants. It enables AI assistants to store, retrieve, and search memories and project code using embeddings and vector search.
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    MIT
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    Enables AI systems to reason through emergent thinking by breaking queries into fragments that interact and form patterns, simulating how insights naturally arise in complex systems. Provides tools for emergent reasoning, pattern analysis, thought comparison, and reasoning session history.
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    SoupNet gives your AI agents one shared memory of how you think β€” across Claude, Cursor, and ChatGPT. Each checks your past decisions as searchable β€œrecipes” and acts on your real judgment. Share it, and your team’s agents inherit that judgment too.
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    A person's falsifiable, consent-based model of how they work best with AI (CMP) β€” read it, refine it, add hunches, and find complementary collaborators. 7 tools.
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    coldstart gives coding agents durable memory of a specific codebase, with no embeddings, no vector store, and no API key. Agents write notes after real tasks β€” what a file is for, how a flow spans files, which invariants hold β€” and those notes are surfaced automatically to a later session whose task matches, so nothing gets rediscovered from scratch. Every note is anchored to real files by content
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    MIT
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    MemOS (Memory Operating System) is a memory management operating system designed for AI applications. Its goal is: to enable your AI system to have long-term memory like a human, not only remembering what users have said but also actively invoking, updating, and scheduling these memories.
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    Apache 2.0
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    An MCP server that records decisions, rejected alternatives, and justifications, and retrieves them later to avoid re-litigating past choices. It stores data locally in SQLite and Markdown.
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    Apache 2.0
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    Enables AI agents to query a local knowledge graph built from document collections using hybrid search (BM25 + vector fusion) and entity-relationship extraction. Supports privacy-first, offline operation with tools for semantic search, entity graph exploration, and corpus statistics.
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