mcp-polaris-ai-datainsight 0.0.7

This tool supports the extraction of text, images, and other elements from various document formats.

mcp-polaris-ai-datainsight

Polaris AI DataInsight is an API service that easily converts documents in various formats into structured data (such as JSON).

This tool supports the extraction of text, images, and other elements from various document formats (e.g., .doc, .docx, .ppt, .pptx, .xls, .xlsx, .hwp, .hwpx).

For more details, please refer to the documentation.

Feature

Extract content from document

Extract text, images, and other elements from various document formats.

• Images in the document are stored on local storage, and the corresponding image paths are included in the JSON output.
• Tables are represented in JSON format, as illustrated in this example.

⚠️ It is recommended to use file_system MCP Server together with this.

file_system is required whenever your workflow needs to

• create directories to store resources, or
• verify existing file paths.

Below is an example configuration how to use file_system with Claude:

{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-filesystem",
        "/path/to/allowed/directory_1",
        "/path/to/allowed/directory_2",
        "..."
      ]
    }
  }
}

Installation and Setup

1. Generate an API key

   • Refer to this guide to generate an API key.

2. Choose an installation method

Method 1: Manual Configuration

Prerequirement: Install uv.

If you prefer a manual setup, add the following configuration to your IDE's MCP config file:

{
  "mcpServers": {
    "datainsight": {
      "command": "uvx",
      "args": ["--no-cache", "mcp-polaris-ai-datainsight@latest"],
      "env": {
        "POLARIS_AI_DATA_INSIGHT_API_KEY": "your-api-key"
      }
    }
  }
}

Method 2: Docker Container

1. Clone repository

   git clone --branch main https://github.com/PolarisOfficeRnD/PolarisAIDataInsight.git
   

   If you want to clone only mcp-polaris-ai-datainsight directory:

   # Git Version >= 2.25
   git clone --filter=blob:none --sparse --branch main https://github.com/PolarisOfficeRnD/PolarisAIDataInsight.git
   

   cd PolarisAIDataInsight
   

   git sparse-checkout set mcp-polaris-ai-datainsight
   

2. Build Docker image:

   cd mcp-polaris-ai-datainsight
   
   docker build . -t mcp-polaris-ai-datainsight
   

3. Use this MCP Server config:

   {
     "mcpServers": {
       "datainsight": {
         "command": "docker",
         "args": [
           "run",
           "-i",
           "--rm",
           "-e",
           "POLARIS_AI_DATA_INSIGHT_API_KEY=your-api-key"
           "mcp-polaris-ai-datainsight",
         ]
       }
     }
   }
   

Method 3: Clone git repository

Preinstall uv and poetry.

1. Clone repository (please refer to Method 4 if you want to clone only mcp-polaris-ai-datainsight directory)
2. Install python dependencies in virtual environment

   cd mcp-polaris-ai-datainsight
   

   uv venv .venv
   
   # Linux
   source .venv/bin/activate
   # Windows
   .venv\bin\activate
   
   
   poetry install --no-root
   

3. Set API Key as environment value and Run server

   # Linux
   export POLARIS_AI_DATA_INSIGHT_API_KEY="your-api-key"
   # Windows
   set POLARIS_AI_DATA_INSIGHT_API_KEY="your-api-key"
   

   python -m mcp_polaris_ai_datainsight.server
   

Output

• Refer to this example for a sample output.
• Alternatively, you can test our API using the playground.