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    Analyzes source code structure across multiple languages using tree-sitter, extracting classes, functions, methods, and metadata with precise line numbers for efficient codebase exploration and AI-assisted development.
    Last updated
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    3
    MIT
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    A local AST and type-aware Go repository context indexer that uses CHA to map symbols, call graphs, dependencies, and architecture patterns. Built for AI coding agents that need to navigate and reason about large Go codebases without reading raw files.
    Last updated
    65
    201
    MIT
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    MCP server that indexes your codebase's public API at startup and serves it via compact tool responses, saving tokens vs reading source files.
    Last updated
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    21
    MIT
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    Provides Python refactoring capabilities via the Rope library, enabling AI agents to perform safe, project-wide code transformations such as renaming symbols, moving modules, and extracting methods.
    Last updated
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    MIT
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    Enables efficient code navigation and retrieval through natural language search, BM25 ranking, and fuzzy matching across multiple programming languages. It drastically reduces token usage by allowing Claude to query specific code symbols and logic instead of reading entire files.
    Last updated
    13
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    13
    MIT
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    Cross-repository code knowledge graph MCP server for Java, Kotlin, JavaScript, and TypeScript. Indexes source code into embedded KuzuDB via tree-sitter and exposes 30+ tools for call-flow tracing, multi-hop taint analysis (OWASP/CWE/PCI/STIG), entry-point reachability filtering, performance hotspot detection, and license compliance — without reading source files. 95% fewer tokens vs source-read
    Last updated
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    1
    MIT
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    AI-powered characterization test generator that reads Python functions or class methods, synthesizes inputs, captures behavior in a sandbox, and emits pytest files to lock legacy code behavior for safe refactoring.
    Last updated
    4
    Apache 2.0
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    Gives coding agents structured code understanding via tree-sitter with 23 tools and 10 languages, enabling precise queries instead of reading entire files.
    Last updated
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    27
    MIT
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    A Model Context Protocol (MCP) server providing 62 AI-optimized tools for .NET/C# semantic code analysis, navigation, refactoring, and code generation using Microsoft Roslyn. Built for AI coding agents - provides compiler-accurate code understanding that AI cannot infer from reading source files alone.
    Last updated
    62
    29
    MIT