API Dash is an open-source, cross-platform API client built with Flutter, offering a lightweight alternative to Postman/Insomnia. It leverages AI for enhanced features, simplifies API request creation and customization for HTTP and GraphQL, provides visual response inspection, and generates integration code.

How It Works

Developed in Flutter for desktop and mobile, API Dash's core innovation is its AI assistant (DashBot) and unique multimedia response preview/download capability (images, PDFs, audio). It supports HTTP, GraphQL, and SSE, with robust import from popular tools.

Quick Start & Requirements

Pre-built binaries are available for macOS, Windows, Linux (.deb, .rpm), and Arch Linux (PKGBUILD). Installation involves downloading the appropriate OS package. Specific hardware/software prerequisites are not detailed. Links to the Application Guide and Installation Guide are provided.

Highlighted Details

• AI-Powered Assistant: Integrates DashBot (local/cloud LLM) for debugging, code generation, and documentation.
• Multimedia Response Preview: Uniquely previews and downloads diverse multimedia API responses (images, PDF, audio, video) beyond text.
• Extensive Code Generation: Offers integration code generation for numerous languages (JavaScript, Python, Kotlin, Dart, C#, Java, etc.).
• Cross-Platform Support: Built with Flutter for desktop (Windows, macOS, Linux) and mobile (iOS/iPad).
• Data Import: Seamlessly imports API collections from Postman, cURL, Insomnia, OpenAPI, and HAR.

Maintenance & Community

Active development is indicated by GSoC participation and a roadmap at Roadmap. Community support is available via a Discord channel. Contribution guidelines are detailed, and a List of Ideas is available.

Licensing & Compatibility

The README does not specify a software license. This omission requires clarification for adoption decisions, especially regarding commercial use or linking with closed-source projects.

Limitations & Caveats

Full support for WebSocket, MQTT, and gRPC is pending. HTML responses offer syntax highlighting but lack web preview. CSV preview is improvable, and the project welcomes contributions for additional multimedia MIME type support.