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"Building a solid memory base for AI development" matching MCP servers:

  • Korea Building Register MCP

    coding-realtor
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    license
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    quality
    D
    maintenance
    Provides 12 tools to query South Korean building register data, including title sheets, floor details, and official house prices via the data.go.kr API. It enables users to perform smart building lookups and region code searches using natural language.
    Last updated
    12
    2
    Apache 2.0

  • ai-memory-mcp

    zhanpu89
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    quality
    C
    maintenance
    Provides persistent session memory for AI assistants, enabling them to store, search, and retrieve conversation summaries across sessions via the Model Context Protocol.
    Last updated
    10
    MIT

  • Memory-MCP

    wb200
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    quality
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    maintenance
    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.
    Last updated
    8
    MIT

  • marm-memory

    Lyellr88
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    license
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    quality
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    maintenance
    MARM MCP provides persistent memory and structured session context beneath any AI tool, so your agents learn, remember, and collaborate across all your workflows.
    Last updated
    14
    320
    Apache 2.0

  • repo-memory

    yubinkim444
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    license
    A
    quality
    B
    maintenance
    A different approach from typical persistent-memory MCPs. Instead of a local SQLite + embeddings store, the memory lives as plain files in a .ai-memory/ directory you commit to your repo (facts.jsonl, decisions/\*.md, gotchas.md). Git is the sync layer — what one Claude/Cursor/Cline learns about a repo, the next session (or a teammate's agent) picks up automatically. 5 MCP tools: get_rep
    Last updated
    5
    1
    MIT

  • anneal-memory

    phillipclapham
    A
    license
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    quality
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    maintenance
    Two-layer memory for AI agents. Episodes compress into identity. The only MCP memory server with an immune system. Patterns earn permanence through evidence, false knowledge gets caught and demoted, and stale information fades — so your agent's memory gets smarter over time, not just bigger. Zero dependencies. 5 tools. Works with any MCP client.
    Last updated
    16
    9
    MIT

  • server-memory

    MK-986123
    F
    license
    A
    quality
    B
    maintenance
    A local-first MCP server for durable agent memory using SQLite and FTS5, enabling knowledge graph storage, search, and recall for AI agents.
    Last updated
    20
    1
  • SAE4U Memory by Simple4uhq

    SAE4U Memoryofficial

    Simple4uhq
    A
    license
    A
    quality
    C
    maintenance
    Provides persistent memory for Claude with hierarchical categorization, cross-corpus recall, session journals, and customizable persona, enabling memory continuity across sessions.
    Last updated
    7
    MIT

  • mcp-memory

    oneKn8
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    license
    A
    quality
    D
    maintenance
    Provides persistent memory with semantic search for MCP-based AI agents, enabling them to store and recall information across sessions using vector embeddings.
    Last updated
    4
    1
    MIT

  • tidbits-memory

    brkhrdt
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    license
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    quality
    C
    maintenance
    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.
    Last updated
    8
    MIT

  • memory-mcp

    chenxiaofie
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    license
    A
    quality
    B
    maintenance
    A persistent memory MCP server for Claude Code that automatically saves conversations and retrieves relevant history across sessions to provide context.
    Last updated
    17
    11
    MIT

  • mcp-memory

    Yarlan1503
    A
    license
    A
    quality
    F
    maintenance
    A drop-in replacement for Anthropic's memory server that utilizes SQLite to ensure data integrity and concurrent access. It enhances the original functionality with semantic search capabilities using vector embeddings and ONNX models.
    Last updated
    11
    1
    MIT