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    Saves the user's exact words as immutable, SHA-256-hashed captures before anything else, then derives events, entities, context cards, and causal hypotheses — every fact traceable to its verbatim source. Local-first personal memory for Claude Code, Codex, and any MCP client.
    13
    3
    MIT
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    Enables AI clients to record research-process artifacts (agents, sources, claims, uncertainty, disagreement, tool usage) and compile a hosted process X-Ray report to inspect what a polished final answer may hide.
    MIT
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    Enables semantic search of the KJV Bible and personal knowledge graph for scripture study, notes, prayers, and memory verses, all running locally with no cloud dependencies.
    MIT
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    An MCP server that manages your conversation context automatically, pruning dead branches and keeping an audit trail of every cut.
    1 npm
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    MIT
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    Enables AI agents to search and modify a personal knowledge base through OAuth-secured MCP tools, covering Obsidian vaults and Google Drive mirrors with semantic search, note read/write operations, audit logging, and eval-gated local classification.
    MIT
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    A local-first personal archive with a read-only MCP gateway that preserves files and AI conversations, derives evidence-linked memory candidates using local models, and enables bounded context retrieval for questions.
    7
    MIT
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    Local RAG system for Claude Code with hybrid search (semantic + BM25), cross-encoder reranking, markdown-aware chunking, and 12 MCP tools. Zero external servers, pure ONNX in-process.
    13
    228 PyPI
    296
    MIT
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    MCP server for the full Pāli Tipiṭaka — ~444,000 segments at parity with SuttaCentral (Sutta + Vinaya + Abhidhamma). Hybrid search, full-sutta fetch with cross-references, segment-aligned translation comparison, and Pāli word lookup. Offered as Dhamma Dāna.
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    MIT
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    Graph-MIND records every conversation you have with Claude Code, Codex and Claude Desktop, word for word, in a store on your own PC. When a question depends on the past, the model you are using calls Graph-MIND over MCP and gets back a few thousand tokens of the conversations that answer it.
    4
    7
    3,169 PyPI
    4
    AGPL 3.0