focus_mcp_data

focus_mcp_data

9
research_and_data

The FOCUS DATA MCP Server allows AI assistants to perform natural language queries on DataFocus data, providing seamless data access and manipulation. It features tools for listing tables, initializing dialogues, and querying data, all in an easy-to-use setting.

FOCUS DATA MCP Server []

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 bearer token

Installation

  1. Clone this repository:
git clone https://github.com/FocusSearch/focus_mcp_data.git
cd focus_mcp_data
  1. 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 config mcp server
  3. use
    1. get table list get table list1 get table list2
    2. Initialize dialogue Initialize dialogue
    3. query: what is the sum salary query

Contact：

https://discord.gg/mFa3yeq9 Datafocus