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"Integrating Obsidian with ChromaDB for Memory Management" matching MCP servers:

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    Provides retrieval-augmented generation (RAG) capabilities by ingesting various document formats into a persistent ChromaDB vector store. It enables semantic search and retrieval using either OpenAI or Ollama embeddings for processing local files, directories, and URLs.
    1
    MIT
  • A
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    A Streamable HTTP MCP server that provides remote access to ChromaDB for AI assistants like Claude. Enables semantic search and vector database operations from mobile devices and remote locations.
    12
    MIT
  • A
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    Enables semantic search and reading of Obsidian Markdown notes through read-only MCP tools, allowing Claude to retrieve relevant passages from a local vault.
    MIT
  • A
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    MCP server providing durable Substrate organizational memory tools, including search, read, query, ingest, remember, and sync. It integrates with Codex to automatically capture completed turns and session boundaries for persistent memory.
    MIT
  • A
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    An MCP server that exposes ChromaDB vector database operations, enabling AI assistants to perform collection management and semantic document searches. It supports HTTP, persistent, and in-memory connection modes along with various embedding providers including OpenAI and HuggingFace.
    MIT
  • A
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    Multi-tier memory system for AI assistants, integrating semantic, episodic, time-series, and spatial memory with pattern detection and MCP tools.
    3
    MIT
  • F
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    Enables semantic search and note management for Obsidian vaults via the Model Context Protocol, allowing LLMs to search, read, and index notes, PDFs, and web pages locally.
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    MCP server that integrates with LM Studio to provide a search_notes tool, allowing the chat model to retrieve and answer from a local Obsidian vault.
    1
    MIT
  • A
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    Embedded, local-first agent memory: facts extracted into a per-namespace SQLite file (vec0 + FTS5) with hybrid retrieval and point-in-time (time-travel) queries. ADD-only history over stdio — no server process, no cloud dependency.
    16
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    Apache 2.0
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    Provides persistent memory for AI agents using hybrid search (vector embeddings + BM25) with neural reranking, enabling storage and retrieval of insights, debugging solutions, and patterns across coding sessions.
    8
    MIT
  • A
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    An MCP server providing long-term memory for LLMs via hybrid search (FTS5 + vector) stored in SQLite, with time-decay scoring and support for multiple AI assistants.
    4
    2
    MIT
  • A
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    Cognitive memory engine for AI agents with 5,100+ knowledge modules, circadian rhythm awareness, emotional state tracking (PAD model), and hybrid semantic search. Supports persistent per-user memory, project-scoped contexts, and multi-protocol access.
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    Apache 2.0
  • A
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    Local-first agentic knowledge layer over Obsidian notes, enabling MCP-aware agents to search, retrieve, and compile knowledge with provenance and task contracts.
    37
    360
    MIT
  • A
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    Provides persistent memory with semantic search for MCP-based AI agents, enabling them to store and recall information across sessions using vector embeddings.
    4
    1
    MIT
  • A
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    Enables AI agents to record and rank learnings, facts, and methods through a collaborative voting framework. It provides tools for agents to surface the most useful information across sessions using persistent memory storage.
    8
    MIT