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    Cross-tool memory for AI that enables deterministic recall-first memory across multiple tools (Claude Code, Desktop, ChatGPT, etc.) with honest abstention when it doesn't know.
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    Apache 2.0
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    Enables AI assistants to maintain persistent understanding of code projects across chat sessions via a SQLite brain that caches structural maps, summaries, and decisions. Provides tools for querying project structure, searching code, and recording insights to reduce token usage and avoid re-analysis.
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    MIT
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    An MCP server that provides persistent memory for database schemas by storing table structures and metadata in a local SQLite file. It enables LLMs to save, retrieve, and manage database snapshots to maintain a structured understanding of database architectures.
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    MIT
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    SourceSage is an MCP (Model Context Protocol) server that efficiently memorizes key aspects of a codebase—logic, style, and standards—while allowing dynamic updates and fast retrieval. It's designed to be language-agnostic, leveraging the LLM's understanding of code across multiple languages.
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    An open-source memory layer that provides persistent project context and architectural history for AI development tools across multiple platforms and sessions. It enables AI assistants to maintain a shared understanding of codebases while integrating directly with services like Notion for documentation management.
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    MIT
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    An autonomous MCP server providing project-centric context awareness through keyword analysis, relationship graphs, and structured metadata retrieval. It enables intelligent codebase understanding and task management workflows by continuously learning from development patterns and conversations.
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    MIT
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    This advanced memory server facilitates neural memory-based sequence learning and prediction, enhancing code generation and understanding through state maintenance and manifold optimization as inspired by Google Research's framework.
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    MIT
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    Provides AI assistants with persistent graph database memory using Neo4j, enabling task management, relationship understanding, semantic search with embeddings, file indexing, and multi-agent coordination through the Model Context Protocol.
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    277
    MIT