Get AI search volume and trends for keywords to understand visibility in ChatGPT and other LLMs.
MIT
519,985 tools. Updated 2026-09-06 08:15
"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
- Get parsed README documentation for any repository by providing its UUID or clone URL. Access clear codebase documentation to understand project structure and purpose.MIT
Matching MCP Servers
- AlicenseNot gradedqualityCmaintenanceProvides a semantic understanding of your codebase by parsing with tree-sitter and building a graph of symbols and dependencies. Enables AI assistants to navigate code, analyze changes, and discover architecture using 18 tools with minimal context overhead.221MIT
- AlicenseAqualityCmaintenanceAn MCP server that recommends UI components and utility methods from private code repositories using AI to enhance code reuse and development efficiency.4161MIT
Matching MCP Connectors
Fetch URLs and return clean Markdown for RAG — nav, ads and boilerplate stripped.
Decision Layer for AI Agents — 58+ tools, Advisor, MCP. Free key: POST /v1/register {}.
- 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
- Retrieve the full schema for PingOne AIC themes, including payload structure, field types, enum values, and constraints, to understand requirements before creating or updating themes.Apache 2.0
- Retrieve codebase context for editing, explaining, or onboarding: locate chunks, map callers/callees, gather related tests, and assess risk in one call.MIT
- Inspect codebase structure, API boundaries, dependencies, and deletion safety. Detect languages, dead code, contracts, and refactoring opportunities to make informed code changes.MIT
- Automates the code validation step, analyzing the codebase to identify implemented security controls and mitigated threats, then generating a markdown report.Apache 2.0
- Retrieve the simplified structure of all flows in a workflow to understand user-drawn diagrams and flowcharts.-
- 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
- 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
- Locate code by natural language meaning, combining semantic vector search with graph analysis to surface relevant files, signatures, and dependencies for initial codebase discovery.MIT
- Retrieve design rules inferred from codebase patterns. Filter by category to understand implicit conventions for spacing, colors, typography, and more before building.Apache 2.0
- Discover server capabilities, supported AWS services, compliance frameworks, and intelligence engines to understand how to use the AWS Security Posture Advisor for security assessments.Apache 2.0
- Generate a comprehensive codebase architecture map showing modules, dependencies, frequently changed files, and API endpoints to understand structure before starting development tasks.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