Upstage MCP Server
About
A Model Context Protocol server for parsing documents using Upstage AI's document digitization API.
Details
- Author
- PritamPatil2603
- GitHub stars
- 3
- Downloads
- 176
- Categories
- Other
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- Document digitization preserving original layout
- Intelligent information extraction with custom schemas
- Supports JPEG, PNG, BMP, PDF, TIFF, HEIC, DOCX, PPTX, XLSX
- Seamless integration with Claude Desktop and other MCP clients
- Auto-generation of extraction schemas
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Upstage MCP ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Install using uv (recommended) or pip, then configure Claude Desktop by adding the server entry to claude_desktop_config.json with your UPSTAGE_API_KEY. After restarting Claude, use the parse_document tool to extract structured content or extract_information to retrieve specific data points from a document.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"upstage mcp server": {
"upstage-mcp-server": {
"command": "uv",
"args": [
"pip",
"install",
"upstage-mcp-server"
]
}
}
}
}McpServers
{
"upstage-mcp-server": {
"command": "uv",
"args": [
"pip",
"install",
"upstage-mcp-server"
]
}
}Upstage MCP Server
> A Model Context Protocol (MCP) server for Upstage AI's document digitization and information extraction capabilities
Overview
The Upstage MCP Server provides a robust bridge between AI assistants and Upstage AI’s powerful document processing APIs. This server enables AI models—such as Claude—to effortlessly extract and structure content from various document types including PDFs, images, and Office files. The package supports multiple formats and comes with seamless integration options for Claude Desktop.
Key Features
- Document Digitization: Extract structured content from documents while preserving layout.
- Information Extraction: Retrieve specific data points using intelligent, customizable schemas.
- Multi-format Support: Handles JPEG, PNG, BMP, PDF, TIFF, HEIC, DOCX, PPTX, and XLSX.
- Claude Desktop Integration: Effortlessly connect with Claude and other MCP clients.
Prerequisites
Before using this server, ensure you have the following:
1. Upstage API Key: Obtain your API key from Upstage API.
2. Python 3.10+: The server requires Python version 3.10 or higher.
3. The MCP server relies upon Astral UV to run, please install
Installation & Configuration
This guide provides step-by-step instructions to set up and configure the upstage-mcp-server
Using uv (Recommended)
No additional installation is required when using uvx as it handles execution. However, if you prefer to install the package directly:
uv pip install upstage-mcp-server
Configure Claude Desktop
For integration with Claude Desktop, add the following content to yourclaude_desktop_config.json:
Configuration Location
- Windows: %APPDATA%\Claude\claude_desktop_config.json
- macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Using uvx Command (Recommended)
{
"mcpServers": {
"upstage-mcp-server": {
"command": "uvx",
"args": ["upstage-mcp-server"],
"env": {
"UPSTAGE_API_KEY": "<your-api-key>"
}
}
}
}
If uvx is not available globally, you may encounter a Server disconnected error. To resolve this, run which uvx to find its full path, and replace "command": "uvx" above with the returned path.
After adding the configuration, restart Claude Desktop to apply the changes.
Output Directories
Processing results are stored in your home directory under:
- Document Parsing Results:
~/.upstage-mcp-server/outputs/document_parsing/
- Information Extraction Results:
~/.upstage-mcp-server/outputs/information_extraction/
- Generated Schemas:
~/.upstage-mcp-server/outputs/information_extraction/schemas/
Local/Development Setup
Follow these steps to set up and run the project locally:
Step 1: Clone the Repository
git clone https://github.com/PritamPatil2603/upstage-mcp-server.git
cd upstage-mcp-server
Step 2: Set Up the Python Environment
```bash
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