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    MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.
    7
    118 PyPI
    49
    MIT
  • A
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    quality
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    Your coding agent remembers how it solved past tasks and reuses it next time: trigger, steps, outcome, lessons. Hooks recall the right skill before a task; skills strengthen with confirmed use and unused ones decay. Local SQLite, no API key, nothing leaves your machine. 9 MCP tools, works with Claude Code, Codex and Cursor. Agent-written memory stays untrusted until you approve it.
    9
    262 PyPI
    11
    Apache 2.0
  • A
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    Helps AI assistants optimize Linux workloads on Arm64 by parsing perf report output, recommending NEON SIMD intrinsics for hot loops, and auditing Python dependency manifests for arm64 wheel availability — all offline and structured.
    4
    Apache 2.0
  • F
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    A local MCP server that provides semantic code search for Python codebases using tree-sitter for chunking and LanceDB for vector storage. It enables natural language queries to find relevant code snippets based on meaning rather than just text matching.
    3
    4
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  • A
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    Enables a model to write short Python programs that call a wrapped MCP server's tools as async functions, rather than invoking them one at a time. The program runs in a locked-down Docker sandbox, and every tool call passes through a host-side bridge that enforces an allowlist, schema-validated arguments, call budgets, timeouts and output caps.
    1
    MIT
  • A
    license
    A
    quality
    C
    maintenance
    Enables efficient analysis of large codebases using Claude Code and Kimi K2.5 through the Model Context Protocol, with session caching and parallel processing to reduce costs and time.
    7
    13 npm
    1
    MIT
  • A
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    quality
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    maintenance
    Enables fast, low-token code search for AI coding agents via a local BM25 engine built on SQLite FTS5, with support for camelCase, snake_case, and Japanese text. Provides a stateless MCP stdio server and a Hermes adapter for multi-agent environments.
    1
    MIT
  • A
    license
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    quality
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    maintenance
    Enables agents to accomplish multi-step work by writing a single sandboxed JavaScript program that drives shell, filesystem, HTTP, and every tool of any configured MCP server, returning only a small summary instead of raw JSON. This collapses dozens of advertised tool schemas into one tool, cutting per-request context by roughly 26× while keeping disabled upstream servers reachable.
    1
    MIT
  • F
    license
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    maintenance
    Enables searching and reading of AI/ML papers from conference proceedings and arxiv, with tools for full-text search, table of contents, and content grep.
    4
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