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    An MCP server that autonomously optimizes ONNX ML models for Arm64 deployment, providing tools to analyze models, apply real INT8 quantization, benchmark performance, and generate Arm64-optimized Docker deployment packages.
    Apache 2.0
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    license
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    Local-first code intelligence MCP server with hybrid BM25 + ONNX vector search, symbol-level impact analysis, diff-aware PR review with risk scoring, and persistent memory tied to git state.
    36
    408
    76
    MIT
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    license
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    quality
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    Knowledge graph for token-efficient code reviews. Builds a structural map of your codebase with Tree-sitter, tracks changes incrementally, and gives AI agents precise context via MCP tools. Features fixed multi-word search, qualified call resolution, dual-mode embedding (ONNX local + LiteLLM cloud), and output pagination.
    7
    64
    Apache 2.0
  • A
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    quality
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    The open retrieval layer for AI agents. Index your entire project — code, docs, legal, research, data — and serve surgical context via MCP. FTS5 full-text search, optional semantic search (FastEmbed/ONNX), 10 built-in parsers, incremental auto-sync.
    22
    MIT
  • A
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    quality
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    Persistent knowledge memory layer for AI agents. Hybrid semantic + full-text search with pgvector, code dependency graph with blast-radius impact analysis, and incremental indexing for 7 languages. In-process ONNX embeddings, no external API required.
    31
    35
    MIT