focus_mcp_data

# FOCUS DATA MCP Server [[中文](./README_CN.md)] 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](https://www.oracle.com/java/technologies/downloads/) - gradle 8.12 or higher. Download [gradle](https://gradle.org/install/) - register [Datafocus](https://www.datafocus.ai/) to obtain bearer token: 1. Register an account in [Datafocus](https://www.datafocus.ai/) 2. Create an application 3. Enter the application 4. Admin -> Interface authentication -> Bearer Token -> New Bearer Token  ## Installation 1. Clone this repository: ```bash git clone https://github.com/FocusSearch/focus_mcp_data.git cd focus_mcp_data ``` 2. Build the server: ```bash 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`): ```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:** ```json { "name": "test", "bearer": "ZTllYzAzZjM2YzA3NDA0ZGE3ZjguNDJhNDjNGU4NzkyYjY1OTY0YzUxYWU5NmU=" } ``` ### 2. gptText2DataInit Initialize dialogue. **Parameters:** - `names` (required): selected table names - `bearer` (required): bearer token - `language` (optional): language ['english','chinese'] **Example:** ```json { "names": [ "test1", "test2" ], "bearer": "ZTllYzAzZjM2YzA3NDA0ZGE3ZjguNDJhNDjNGU4NzkyYjY1OTY0YzUxYWU5NmU=" } ``` ### 3. gptText2DataData Query data results. **Parameters:** - `chatId` (required): chat id - `input` (required): Natural language - `bearer` (required): bearer token **Example:** ```json { "chatId": "03975af5de4b4562938a985403f206d4", "input": "max(age)", "bearer": "ZTllYzAzZjM2YzA3NDA0ZGE3ZjguNDJhNDjNGU4NzkyYjY1OTY0YzUxYWU5NmU=" } ``` ## Response Format All tools return responses in the following format: ```json { "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](https://discord.gg/mFa3yeq9)