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    Gives AI coding agents persistent, evolving knowledge about a codebase, enabling them to store and retrieve observations about architecture, conventions, gotchas, and recent work context.
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    MIT
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    Enables storing and querying structured information about software code entities (classes, functions, files) and their relationships (calls, imports) along with qualitative observations like design decisions and change rationale.
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    MIT
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    Enables Claude to maintain persistent memory across conversations using a local knowledge graph with fuzzy search capabilities, allowing it to remember and recall information about users, relationships, and context.
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    A Model Context Protocol server that provides knowledge graph-based persistent memory for LLMs, allowing them to store, retrieve, and reason about information across multiple conversations and sessions.
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    MIT
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    Daem0n-MCP provides AI agents with persistent, semantically indexed memory to track decisions, rules, and outcomes across sessions. It actively prevents repetitive mistakes by enforcing context checks and prioritizing information about past failures during recall. Best for Claude Code.
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    MIT
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    Provides Claude with a knowledge base about the Choice restaurant platform, enabling natural language queries about products, pricing, integrations, and features.
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    MCP Memory is an MCP Server that gives MCP Clients the ability to remember information about users across conversations. It uses vector search technology to find relevant memories based on meaning, not just keywords.
    11
    MIT
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    Secure MCP server for querying Google NotebookLM notebooks. Enables AI assistants to list notebooks, read sources, and ask the NotebookLM AI questions about your sources.
    15
    MIT
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    MCP Memory is a MCP Server that gives MCP Clients the ability to remember information about users across conversations using vector search.
    11
    MIT
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    Enables AI assistants to interact with Anytype knowledge base via natural language, with Docker-based HTTP transport for always-on background operation.
    1
    MIT
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    Enables querying a Neo4j knowledge graph about Wroclaw University of Science and Technology using natural language. Converts user questions into Cypher queries and retrieves contextual information through an intelligent RAG pipeline with LLM-powered query routing.
    5