"Dart" matching MCP servers:

A Model Context Protocol (MCP) server that provides Dart language analysis capabilities to Claude Code, enabling real-time diagnostics, code navigation, and symbol search for Dart projects.

Local-first MCP server providing deterministic Flutter/Dart static analysis, knowledge search, and project review with structured insights and confidence-based findings over an indexed SQLite store of official repositories.

An MCP server for static Big-O time complexity analysis using tree-sitter AST parsing. Supports JavaScript, TypeScript, Python, Java, Kotlin, and Dart.

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

MCP server that gives coding agents right-to-left awareness with tools to lint RTL code, normalize Arabic text, and detect text direction.

Enables MCP-compatible agents to audit an entire repository through one question, detecting stacks and running parallel checks for dead code, dependencies, security, CVEs, complexity, and lint across Laravel/PHP, Python, TypeScript/React, and Flutter/Dart. It returns normalized, severity-sorted findings with false positives flagged and secret values kept out of the output.

Enables LLMs to develop, debug, test, and manage SAP ABAP objects on a live system through the ABAP Development Tools (ADT) protocol.

Enables semantic and hybrid search over documents and codebases backed by a Qdrant vector database, with collection management, document CRUD, metadata filtering, and AST-aware code indexing using local or cloud embedding providers. Supports natural language queries, incremental re-indexing of changed files, and custom configurable prompts for guided workflows.

ghidraMCP is an MCP server that allows LLMs to autonomously reverse engineer applications by exposing core Ghidra functionality as tools for MCP clients.

An MCP server that folds function and class implementations into structural skeletons while preserving signatures, interfaces, and docstrings, reducing tokens by up to 90%+ for AI agents. Exposes tools to get repository skeletons, unfold specific symbols on demand, and retrieve exact token and prompt cost savings metrics.

Enables AI assistants to safely read and search project files within a configured root directory, supporting regex search, file listing, line-range reading, and symbol usage lookup.