"A platform for finding maps or navigation tools by TomTom" matching MCP servers:

A minimal MCP server providing a normalized API for code navigation and repository inspection through tools like symbol searching and call tracing. It enables AI agents to perform structured analysis of codebases by mapping endpoints, inspecting file trees, and tracing symbol relationships.

Analyzes codebases for cross-platform compatibility issues, detecting platform-specific APIs, file path problems, line ending inconsistencies, and shell command incompatibilities across Windows, macOS, and Linux.

An MCP server that provides a persistent sandbox for AI coding agents to explore codebases server-side, returning only compact summaries to reduce context consumption.

A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Local MCP servers that give Claude Code access to other tools mid-session.

Provides tools for Python code navigation, analysis, and refactoring, including finding definitions, references, and symbol lists. It enables automated tasks such as renaming symbols and organizing imports to enhance AI-driven development.

Integrates AI into software development workflows by providing three MCP tools: code review checklists, conventional commit message generation, and API documentation formatting from docstrings. Connects to Claude Desktop and any MCP-compatible client.

A Model Context Protocol (MCP) server that provides TypeScript development tools for automated refactoring and code analysis.

Enables interaction with the Flutter SDK by providing tools to analyze and apply fixes to Dart and Flutter files.

Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.

MCP server providing npm registry search, package details, dependency auditing, bundle size estimation, and package comparison tools for AI agents.

A Model Context Protocol server that provides tools to find regex pattern positions in files and list allowed directories, enabling text analysis with LSP-like functionality.

Provides AI assistants with frontend development tools including component scaffolding, bundle analysis, accessibility checks, and responsive design guidance. Enables automated generation of React components with tests and stories, bundle optimization recommendations, and WCAG compliance fixes.

A Model Context Protocol (MCP) server designed to easily dump your codebase context into Large Language Models (LLMs).

Enables AI agents to format SQL, explain queries in plain English, analyze schemas, build queries from natural language, and generate migrations, all without requiring a database connection.

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.

A Python framework that exposes developer tools through MCP, REST API, and CLI from a single shared registry, enabling AI assistants, HTTP clients, and terminal users to access the same tools.

Enables AI agents to explore, analyze, and search file systems, with tools for directory trees, file statistics, duplicate detection, code counting, and multi-criteria file search.

Provides AI-callable tools for modernizing legacy applications, including stack detection, API contract extraction, SQL to Flyway conversion, and migration effort estimation.