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focus_mcp_data
Le plugin de requête de données intelligent sous DataFocus qui prend en charge les conversations multi-rondes fournit des capacités de chatbi plug-and-play.
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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 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
- vsCode install cline plugin
- mcp server config
- use
- get table list
- Initialize dialogue
- query: what is the sum salary
- get table list
Contact:
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Reviews

user_o1c4Onmm
As a dedicated user of focus_mcp_data, I am thoroughly impressed by its performance and ease of use. The tool, developed by FocusSearch, excels in managing and processing multi-channel point data effectively. The clear and concise documentation on their GitHub page (https://github.com/FocusSearch/focus_mcp_data) makes it easy to navigate and utilize all features. It's an invaluable resource for anyone dealing with complex data analysis. Highly recommend!