Datafocus

Interface with Datafocus data tables via natural language.

Installation Instructions

README: https://github.com/FocusSearch/focus_mcp_data

FOCUS DATA MCP Server [中文]

A Model Context Protocol (MCP) server enables artificial intelligence 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 to) the data tables to be analyzed.
• Select Datafocus data table initialization dialogue
• Natural language data acquisition results

Prerequisites

• jdk 23 or higher. Download jdk
• gradle 8.12 or higher. Download gradle
• register Datafocus to obtain bearer token:
  1. Register an account in Datafocus
  2. Create an application
  3. Enter the application
  4. Admin -> Interface authentication -> Bearer Token -> New Bearer Token

Installation

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 jar path: build/libs/focus_mcp_data.jar

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 table list in datafocus.

Parameters:

• name (optional): table name to filter
• bearer (required): bearer token

Example:

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

2. gptText2DataInit

Initialize dialogue.

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 results.

Parameters:

• chatId (required): chat id
• input (required): Natural language
• bearer (required): bearer token

Example:

{
  "chatId": "03975af5de4b4562938a985403f206d4",
  "input": "max(age)",
  "bearer": "ZTllYzAzZjM2YzA3NDA0ZGE3ZjguNDJhNDjNGU4NzkyYjY1OTY0YzUxYWU5NmU="
}

Response Format

All tools return responses in the following format:

{
  "errCode": 0,
  "exception": "",
  "msgParams": null,
  "promptMsg": null,
  "success": true,
  "data": {
  }
}

Visual Studio Code Cline Sample

1. vsCode install cline plugin
2. mcp server config
3. use
   1. get table list
   2. Initialize dialogue
   3. query: what is the sum salary

Contact：

https://discord.gg/mFa3yeq9