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465,316 tools. Updated 2026-08-19 03:33

"Code intelligence tools for LLMs to understand codebase structure and locate functionality" matching MCP tools:

  • Search an indexed codebase with natural language to locate functions, classes, and patterns. Understand dependencies and explore existing systems.
    Apache 2.0
  • Search codebase for code structure using Tree-sitter AST patterns. Scans all files to match structural elements like functions or classes. Requires glob to limit scope.
    MIT
  • Analyze token or smart contract addresses to retrieve comprehensive intelligence reports including price, market data, security flags, liquidity, and source code for EVM and Solana chains.
    MIT
  • Get a comprehensive overview of any codebase—structure, frameworks, entry points, file types, and more—in a single call. Ideal for quickly orienting yourself in an unfamiliar project.
    MIT
  • Find code by meaning across your entire codebase using natural language queries or code snippets, returning relevant chunks with file paths and line numbers.
    Apache 2.0

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  • Return a bounded map of directories and files for one repository, enabling you to understand its structure before choosing files. Specify max depth and entries to control scope.
    MIT
  • Analyze a repository to reveal project type, languages, file sizes, module dependencies, and circular import warnings. Use this to understand the codebase structure before making changes.
    AGPL 3.0
  • Retrieve design rules inferred from your codebase patterns to understand implicit conventions. Filter by category (spacing, colors, typography, borderRadius, naming, components) for targeted insights.
    Apache 2.0
  • Locate code by meaning and structure using hybrid semantic-graph search. Returns files, signatures, and dependencies for initial codebase discovery.
    MIT
  • Analyze codebase structure and extract function/class signatures to understand project organization and locate relevant code components.
    MIT
  • Access the JSON protocol specification to understand envelope structure, exit codes, and command metadata. Use before other tools to interpret response formats and error semantics.
    MIT
  • Get file structure, size, and semantic outline for large files to understand their organization and key components quickly.
    MIT
  • Scans a project directory to produce a structural overview including language, framework, dependencies, and entry points. Use this to understand codebase architecture before diving deeper.
    MIT