Showing 5 open source projects for "note taking"

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    A low-code dashboard makes monitoring intuitive for any admin, while scripting and custom sensors give experts full control.

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  • 1
    Zettelkasten MCP

    Zettelkasten MCP

    Implements the Zettelkasten knowledge management methodology

    The Zettelkasten MCP Server is a Model Context Protocol (MCP) server that implements the Zettelkasten knowledge management methodology. It allows users to create, link, and manage notes, facilitating a structured and interconnected note-taking system. ​
    Downloads: 6 This Week
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  • 2
    Open Notebook

    Open Notebook

    An Open Source implementation of Notebook LM with more flexibility

    Open Notebook is an open-source, privacy-focused alternative to Google’s Notebook LM that gives users full control over their research and AI workflows. Designed to be self-hosted, it ensures complete data sovereignty by keeping your content local or within your own infrastructure. The platform supports 16+ AI providers—including OpenAI, Anthropic, Ollama, Google, and LM Studio—allowing flexible model choice and cost optimization. Open Notebook enables users to organize and analyze...
    Downloads: 48 This Week
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  • 3
    claude-obsidian

    claude-obsidian

    Claude + Obsidian knowledge companion

    ...The system follows the LLM Wiki pattern, where information is stored as persistent markdown files that grow richer over time through cross-referencing and synthesis. It includes features such as contradiction detection, orphaned note identification, and automatic indexing. A persistent memory layer ensures continuity across sessions, eliminating the need for repeated context. It also performs autonomous research to fill knowledge gaps and expand the knowledge base. Overall, it turns note-taking into an active, compounding intelligence system.
    Downloads: 7 This Week
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  • 4
    Mem0

    Mem0

    The Memory layer for AI Agents

    Mem0 is a self-improving memory layer designed for Large Language Model (LLM) applications, enabling personalized AI experiences that save costs and delight users. It remembers user preferences, adapts to individual needs, and continuously improves over time. Key features include enhancing future conversations by building smarter AI that learns from every interaction, reducing LLM costs by up to 80% through intelligent data filtering, delivering more accurate and personalized AI outputs by...
    Downloads: 4 This Week
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    MongoDB Atlas runs apps anywhere

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  • 5
    trimwise

    trimwise

    Query-aware prompt compression for high-signal LLM prompts.

    ...It selects useful fragments from across the document, returns them in source order, and guarantees that the measured result stays within your token, word, or character limit. This is especially useful when an agent has several sources but cannot place every source in the context window. Instead of taking the first N characters from each article, report, note, or search result, Trimwise gives each source a smarter evidence budget while leaving your system prompt, instructions, examples, and output schema untouched.
    Downloads: 0 This Week
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