Tiny Chat

by to-aoki

2 stars

363 downloads

Not rated

GitHub

About

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.

Details

Author: to-aoki
GitHub stars: 2
Downloads: 363
Categories: Communication, Other, Database, AI, Knowledge Base

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name Tiny Chat

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

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

JSON

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

JSON

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

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

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

JSON

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

JSON

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

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

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

JSON

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

JSON

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

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

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

JSON

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

JSON

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

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

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

JSON

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

JSON

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

From the repository

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.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

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

McpServers

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

# Build the package pip install build python -m build # Install the built package pip install dist/*.whl

streamlit run tiny_chat/main.py --server.address=127.0.0.1

streamlit run tiny_chat/main.py --server.address=127.0.0.1 -- --database

{ "mcpServers": { "tiny-chat": { "command": "/path/to/tiny_chat/.venv/bin/tiny-chat-mcp", "env": { "DB_CONFIG": "/path/to/tiny_chat/database_config.json" } } } }

model: target search qdrant collection name (model change in conversation).

curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{"model": "qdrant-collection-name", "messages": [{"role": "user", "content": "カレーライスの材料は？"}]}'

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Details

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Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

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