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tuui

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Basic Information

TUUI is a desktop LLM chat application and MCP (Model Context Protocol) client that provides a unified user interface for integrating and orchestrating cross‚Äëvendor large language model APIs. The repository presents a complete project scaffold that was largely assembled with AI assistance and enforces strict linting and naming conventions to control quality of generated code. TUUI is intended to accelerate AI tool adoption by exposing MCP primitives, visualizations and local desktop extensions while offering a UI for configuring multiple LLM backends, managing state, and running automated tests. The project includes TypeScript support, a Pinia-based global store, Vue/Vuetify UI components, and editable JSON configuration templates for LLM endpoints and models. It also documents platform prerequisites and tips to run remote or local MCP servers and to troubleshoot known MCP server issues.

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913
App URL
https://github.com/AI-QL/tuui
Github Repository
https://github.com/AI-QL/tuui/blob/main/README.md

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App Details

Features
The README documents several core features: MCP-based tool integration to accelerate cross‚Äëvendor LLM orchestration, dynamic LLM API configuration via JSON templates, and support for multiple chatbot entries. The app surface includes MCP primitive visualization, tool call tracing and selectable tool selection to control function/tool invocation. It supports desktop extensions (.dxt), configurable sampling and sampling presets, LLM API setting management, data insights and native devtools for debugging. The codebase provides TypeScript support, multilingual UI, a basic layout manager and global state via Pinia. It also offers automated application testing support, guidance for remote MCP servers (mcp-remote), and example configurations and types for LLM connections.
Use Cases
TUUI helps developers and advanced users connect, configure and debug heterogeneous LLM backends from a single desktop client so teams can prototype and orchestrate multi‚Äëvendor workflows. It centralizes LLM configurations and stores them locally, provides visual traces of tool calls and sampling choices to aid analysis, and exposes primitives for inspecting MCP interactions. The project documents required runtime environments (Node.js for NPX servers, Python and UV for UVX servers, Docker for containerized servers) and offers guidance for running remote MCP servers and resolving common MCP server spawn/auth issues. TUUI also supplies testing and linting guidance to maintain safety and code quality in an AI-generated codebase and encourages community contributions for UI, docs and feature improvements.

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