"Flutter and Dart source code repositories" matching MCP servers:

A real-time server that provides Flutter/Dart documentation and pub.dev package information to AI assistants, ensuring they generate accurate and up-to-date Flutter code.

Connects AI coding clients to a running Flutter app's Dart VM Service so they can stream live exceptions with stack traces, logs, network calls, frame timings, memory, rebuild attribution and navigation state as structured tool results. It also correlates that evidence into root-cause diagnoses with confidence and suggested fixes, and streams everything to a browser dashboard.

dart-mcp

Enables building Flutter and Dart apps through a multi-agent system that orchestrates specialized agents for UI design, backend development, testing, and deployment.

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

Gives AI coding agents live, cached access to current Flutter, Dart SDK and pub.dev documentation returned as clean markdown, resolving class names, identifiers and packages on demand instead of relying on a model's memory. Also provides ranked name search over thousands of classes and a politeness layer with robots.txt compliance, throttling, conditional GETs and request budgets.

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.

Enables debugging Flutter apps on Android by exposing the widget tree and source locations, supporting hot reload and pixel-level UI diffs, along with filtered Android logs, crash traces, and device interaction.

An MCP server that enables Claude to perform financial analysis and visualization of Korean listed companies using the DART API. It supports detailed financial metrics, business unit sales breakdowns, and company comparisons for KOSPI and KOSDAQ stocks.

A distributable Model Context Protocol (MCP) server that exposes Dart SDK commands for AI-powered development. This server bridges the gap between AI coding assistants and Dart/Flutter development workflows by implementing the Model Context Protocol (MCP).

Provides Flutter best practices, code analysis, and state management recommendations for senior developers.

Enables Android APK reverse engineering and Flutter runtime injection through a six-step pipeline of decompile, analyze, synthesize, inject, patch, and repackage. Provides MCP tools for authorized security research and penetration testing.

Exposes structured Microsoft Dynamics 365 Business Central source code (versions 23-29, 47 localizations) to AI agents via MCP, enabling fast lookups, searches, and code analysis.

Enables precise search of financial statement footnotes from Korean DART electronic disclosure, filtering by market, industry, and topic with high precision through rule-based topic matching.

An MCP server that wraps Flutter CLI tools into structured, agent-friendly tools for AI coding agents, with features like two-phase test results, output capping, and managed app lifecycle.

MCP server for searching, browsing, and analyzing decompiled Minecraft source code locally. Supports symbol lookup, text search, reference lookup, and lightweight RAG.

Enables AI assistants to search Korean DART corporate disclosures, financial statements, ownership filings, and fully parsed XBRL, while converting HWP/PDF attachments into markdown. It also provides analyst-style frames such as insider trading signals, accounting-risk scoring, and Buffett-style quality checklists for comparing companies.

An MCP server that enables AI assistants to navigate, search, and analyze local Keycloak source code to support developer customizations like SPIs and authenticators. It provides tools for searching classes, generating boilerplate code, detecting breaking changes between versions, and tracing dependencies.

Enables reproducible evaluation of AI agents on multi-source evidence investigation tasks, providing Docker-based scenarios, MCP tools, and automated scoring for payout reconciliation, performance-claim verification, and incident reconstruction.

Provides on-demand access to AOSP and Jetpack source code to help AI understand Android framework internals. It features a hybrid architecture using Tree-sitter and LSP for precise code extraction, cross-file navigation, and local source indexing.