Focus MCP Data

🚀 FOCUS DATA MCP Server

A Model Context Protocol (MCP) server that enables AI assistants to directly query data results. Users can obtain data results from DataFocus using natural language.

🚀 Quick Start

This MCP server allows AI assistants to directly query data results. Users can obtain data results from DataFocus using natural language.

✨ Features

• Register on DataFocus to open an application space and import (directly connect) the data tables to be analyzed.
• Select a Datafocus data table to initialize a conversation.
• Use natural language to obtain data results.

📦 Installation

Prerequisites

• JDK 23 or higher. Download JDK.
• Gradle 8.12 or higher. Download Gradle.
• Register on Datafocus to obtain a Bearer token:
  1. Register an account on Datafocus.
  2. Create a new application.
  3. Enter the application.
  4. Management -> Interface Authentication -> Bearer Token -> New Bearer Token.

Steps

1. Clone this repository:

git clone https://github.com/FocusSearch/focus_mcp_data.git
cd focus_mcp_data

2. Build the server:

gradle clean
gradle bootJar

The path of the generated jar: build/libs/focus_mcp_data.jar

📚 Documentation

MCP Configuration

Add the server to your MCP settings file (usually located at ~/AppData/Roaming/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json):

{
  "mcpServers": {
    "focus_mcp_data": {
      "command": "java",
      "args": [
        "-jar",
        "path/to/focus_mcp_data/focus_mcp_data.jar"
      ],
      "autoApprove": [
        "tableList",
        "gptText2DataInit",
        "gptText2DataData"
      ]
    }
  }
}

Available Tools

1. tableList

Get the list of tables in DataFocus.

Parameters:

• name (optional): Table name filter.
• bearer (required): Bearer token.

Example:

{
  "name": "test",
  "bearer": "ZTllYzAzZjM2YzA3NDA0ZGE3ZjguNDJhNDjNGU4NzkyYjY1OTY0YzUxYWU5NmU="
}

2. gptText2DataInit

Initialize a conversation.

Parameters:

• names (required): Selected table names.
• bearer (required): Bearer token.
• language (optional): Language ['english','chinese'].

Example:

{
  "names": [
    "test1",
    "test2"
  ],
  "bearer": "ZTllYzAzZjM2YzA3NDA0ZGE3ZjguNDJhNDjNGU4NzkyYjY1OTY0YzUxYWU5NmU="
}

3. gptText2DataData

Query data using natural language.

Parameters:

• question (required): User's question.
• bearer (required): Bearer token.

Example:

{
  "question": "Show the information of all employees",
  "bearer": "ZTllYzAzZjM2YzA3NDA0ZGE3ZjguNDJhNDjNGU4NzkyYjY1OTY0YzUxYWU5NmU="
}

Response Format

The server will return the following JSON format:

{
  "code": 200,
  "message": "Success",
  "data": {
    // The specific data varies according to the request.
  }
}

If an error occurs, the corresponding error code and message will be returned.

📄 Contact Information

https://discord.gg/mFa3yeq9