Https://github.com/FocusSearch/focus_mcp_data
FocusSearch/focus_mcp_data · 14 stars · Java · Apache-2.0
MCP server The intelligent data query tool under DataFocus that supports multi-round conversations provides plug-and-play ChatBI capabilities.
Install
The repo has no one-line install. Follow its README.
Files
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:
- Register an account in Datafocus
- Create an application
- Enter the application
- Admin -> Interface authentication -> Bearer Token -> New Bearer Token

Installation
- Clone this repository:
git clone https://github.com/FocusSearch/focus_mcp_data.git cd focus_mcp_data
- 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 filterbearer(required): bearer token
Example:
{
"name": "test",
"bearer": "ZTllYzAzZjM2YzA3NDA0ZGE3ZjguNDJhNDjNGU4NzkyYjY1OTY0YzUxYWU5NmU="
}
2. gptText2DataInit
Initialize dialogue.
Parameters:
names(required): selected table namesbearer(required): bearer tokenlanguage(optional): language ['english','chinese']
Example:
{
"names": [
"test1",
"test2"
],
"bearer": "ZTllYzAzZjM2YzA3NDA0ZGE3ZjguNDJhNDjNGU4NzkyYjY1OTY0YzUxYWU5NmU="
}
3. gptText2DataData
Query data results.
Parameters:
chatId(required): chat idinput(required): Natural languagebearer(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
Contact:
Facts
- Kind
- MCP server
- Group
- Uncategorized
- Stars
- 14
- License
- Apache-2.0
- Language
- Java
- Last push
- 2025-04-14
- Forks
- 4
- Homepage
- www.datafocus.ai
- Topics
- nl2sql, text2sql
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