Chat2API (xiaoY233/Chat2API) is an open-source AI project on GitHub. Repository summary: Chat2API enables zero-cost access to leading AI models by leveraging official web UIs. It supports providers such as DeepSeek, GLM, Kimi, MiniMax, Qwen, and Z.ai, and seamlessly integrates with tools like openlcaw, Cline, and Roo-Code. Its focus includes MCP and tool-calling integration, retrieval-augmented generation, developer-centric engineering workflows. It is suitable for extension, integration, and iterative delivery in real workflows.
License
Other
Stars
902
Homepage
https://chat2api-doc.vercel.app/Features
- Core capability: Chat2API enables zero-cost access to leading AI models by leveraging official web UIs. It supports providers such as DeepSeek, GLM, Kimi, MiniMax, Qwen, and Z.ai, and seamlessly integrates with tools like openlcaw, Cline, and Roo-Code.
- Provides MCP or tool-calling integration
- Supports vector retrieval and retrieval-augmented reasoning
- Built for code generation, debugging, or engineering integration
- Repository: xiaoY233/Chat2API
- Primary language: TypeScript
Use Cases
- Connects external systems into agent workflows
- Builds enterprise knowledge Q&A and document retrieval systems
- Supports AI engineering build-and-iterate workflows for dev teams
- Build internal AI workflow prototypes with Chat2API
- Validate Chat2API in production-like engineering scenarios
- Building AI development workflows
FAQ
Teams should first define integration boundaries and call patterns, then map repository capabilities into concrete interfaces, parameters, and access rules. GitHub repository: https://github.com/xiaoY233/Chat2API. Community traction is around 901 stars. License: Other.
It usually works as an execution component or capability layer, with common deployment fits such as: Connects external systems into agent workflows, Builds enterprise knowledge Q&A and document retrieval systems, Supports AI engineering build-and-iterate workflows for dev teams.
