Tiny Chat

Name: Tiny Chat
Author: to-aoki

@to-aoki

关于 Tiny Chat

This is an LLM application with chat functionality, featuring chat using RAG, a database, and MCP server capabilities. The UI is designed for Japanese users.

#chat #continue #rag #qdrant #mcp-server #openai-like

基本信息

分类

AI 与智能体

许可证

MIT

运行时

python

传输方式

stdio

发布者

to-aoki

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "tiny_chat": {
      "command": "python",
      "args": [
        "-m",
        "build"
      ]
    }
  }
}

工具

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概览

What is Tiny Chat?

Tiny Chat is a chat application with an MCP (Model Context Protocol) server, a web interface, and an OpenAI-compatible RAG API. It integrates with Qdrant for retrieval-augmented generation and supports local databases. It is intended for developers and Claude Desktop users who need a self-hosted chat system with retrieval capabilities.

How to use Tiny Chat?

Install the package via pip, then run the web interface using tiny-chat (or streamlit run tiny_chat/main.py for development). Configure the MCP server in Claude Desktop by specifying the path to the tiny-chat-mcp binary and a DB_CONFIG environment variable. Alternatively, start the OpenAI Chat API RAG server with tiny-chat-api and query it using the model name set to a Qdrant collection name.

Key features of Tiny Chat

Web interface built with Streamlit
MCP server integration for Claude Desktop
OpenAI-compatible Chat Completions API
RAG (Retrieval-Augmented Generation) using Qdrant
Local database support (with DB_CONFIG)

Use cases of Tiny Chat

Provide a local chat interface with RAG knowledge retrieval
Connect Claude Desktop to a custom Qdrant-backed knowledge base
Serve as an OpenAI-compatible backend for custom frontend applications
Run a minimal chat system with or without a database

FAQ from Tiny Chat

What Python version is required?

Tiny Chat is tested with Python 3.10 or later.

How do I set up the MCP server for Claude Desktop?

Add a JSON entry to your Claude Desktop configuration with the command pointing to the tiny-chat-mcp binary and the environment variable DB_CONFIG set to the database configuration file path.

What does the `model` parameter do in the API?

The model parameter in the Chat Completions request specifies the target Qdrant collection name. Changing the model changes which collection is searched.