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    Knot is a semantic and structural codebase indexer designed for AI coding agents and developers navigating large projects. It combines vector search and graph traversal to find code by meaning, analyze impact via reverse dependencies, and explore file architectures.
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    MIT
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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.
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    A field-level semantic change impact analysis MCP server for Claude Code, enabling natural language queries to find affected code when modifying fields, strings, or functions across multiple languages.
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    MIT
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    Enables efficient codebase exploration with tools to list exports, get file outlines, read targeted regions, and find references without loading entire files.
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    Assigns personality types to functions, rates variable name energy, and suggests aesthetic alternatives for code, providing an unscientific yet entertaining vibe assessment.
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    MIT
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    Provides project-wide semantic PHP refactoring tools (find references, rename classes/members, move class, class info) for AI assistants by wrapping Phpactor.
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    ISC
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    Provides intelligent semantic code search using local AI embeddings, enabling natural language queries to find relevant code by meaning rather than exact keywords. Indexes codebases in the background with smart project detection and privacy-first local processing.
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    MIT
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    MCP server providing dependency and package management tools for AI agents. Analyze licenses, find outdated packages, visualize dependency trees, estimate bundle sizes, and audit security vulnerabilities.
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    MIT
  • F
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    An MCP server that enables AI to interact with the private 'my-design' React component library and design tokens for UI generation and technical support. It provides tools for component searching, API documentation retrieval, and migration guidance based on specific internal design specifications.
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    Exposes technical debt management to AI coding assistants, enabling them to find, prioritize, and resolve TODO/FIXME/BUG comments across codebases via MCP tools.
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    MIT
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    Indexes any TypeScript / React / Next.js repo into a queryable code graph and exposes 13 MCP tools — who-renders, who-calls, find-references, blast-radius, find-cycles, dead-code orphans, and local semantic search — so agents query structure instead of reading whole files. Built on ts-morph, so edges are resolved, not grepped.
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    MIT
  • A
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    Enables agents to quickly find and edit code in a codebase with surgical precision. Find symbols, edit them everywhere with tools for reading code blocks, searching/replacing text, and making precise line-based modifications.
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    An MCP server for React Native Upgrade Helper diffs. It fetches the same generated template diffs used by React Native Upgrade Helper, backed by react-native-community/rn-diff-purge, and exposes them as MCP tools that agents can call directly.
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    MIT
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    Chat with your codebase through intelligent code searching without embeddings by breaking files into logical chunks, giving the LLM tools to search these chunks, and letting it find specific code needed to answer your questions.
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    MIT
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    Enables intelligent code analysis and search across repositories using the CodeRank algorithm (inspired by PageRank) to identify critical modules, trace dependencies, find code hotspots, and perform context-aware keyword searches with importance-ranked results.
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    Apache 2.0
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    Enables AI agents to perform semantic search over codebases by converting natural language queries into efficient search patterns like grep and ripgrep. It utilizes LLMs to verify relevance and find code snippets that traditional keyword-based searches might miss.
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    Exposes Language Server Protocol (LSP) tools such as diagnostics, goto definition, find references, symbols, and rename as a stdio MCP server.
    6
    MIT