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AI Memory Hub

by vib28
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    • Brainstem

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      Local-first knowledge backend for AI agents that connects MCP hosts to an Obsidian-compatible vault with indexed retrieval, token-budgeted memory recall, and secure ingestion.
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    • obsidian_mcp

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      Enables reading, writing, searching, and managing Obsidian vault notes through MCP tools and prompts, allowing AI agents to interact with local knowledge bases.
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    • vault-mcp

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      Serves as a unified MCP gateway to an Obsidian vault, enabling AI agents to perform hybrid lexical/vectorial semantic search, explore note graphs, and write through consent-based intent batches with conflict detection.
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    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A3.7/5.0

    Scored across 8 tools

    Disambiguation5/5

    Each tool targets a distinct operation: policy introspection, search, file read, write/propose, update/supersede, delete, integrity audit, and index rebuild. Memory_search vs memory_read and propose vs supersede are related but clearly separated by descriptions.

    Naming Consistency5/5

    All tools share a consistent memory_ prefix and use clear snake_case action suffixes such as search, read, propose, supersede, forget, audit, and reindex. The pattern is predictable and uniform.

    Tool Count5/5

    Eight tools is well within the ideal range and appropriate for a persistent memory hub. Each tool covers a distinct lifecycle or maintenance need without unnecessary bloat.

    Completeness4/5

    The core memory lifecycle is well covered: policy, search, read, create/propose, update/supersede, delete, audit, and reindex. The only minor gap is that review-mode approvals/rejections have no dedicated tool, though this is likely handled outside the agent workflow.

    Maintenance

    ActivityMaintained
    ResponsivenessResponsive

    Resources