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.github/workflows/python-publish.yml

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runs-on: ubuntu-latest
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environment:
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name: pypi
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url: https://pypi.org/p/upstage-mcp-server
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url: https://pypi.org/p/mcp-server-upstage
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permissions:
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id-token: write
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.github/workflows/test-publish.yml

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runs-on: ubuntu-latest
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environment:
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name: test-pypi
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url: https://test.pypi.org/p/upstage-mcp-server
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url: https://test.pypi.org/p/mcp-server-upstage
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steps:
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- uses: actions/checkout@v4

README.md

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@@ -24,13 +24,13 @@ Before using this server, ensure you have the following:
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## Installation & Configuration
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This guide provides step-by-step instructions to set up and configure the upstage-mcp-server
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This guide provides step-by-step instructions to set up and configure the mcp-server-upstage
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### Using `uv` (Recommended)
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No additional installation is required when using `uvx` as it handles execution. However, if you prefer to install the package directly:
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```bash
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uv pip install upstage-mcp-server
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uv pip install mcp-server-upstage
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```
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## Configure Claude Desktop
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```json
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{
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"mcpServers": {
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"upstage-mcp-server": {
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"mcp-server-upstage": {
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"command": "uvx",
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"args": ["upstage-mcp-server"],
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"args": ["mcp-server-upstage"],
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"env": {
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"UPSTAGE_API_KEY": "<your-api-key>"
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}
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Processing results are stored in your home directory under:
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- **Document Parsing Results:**
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`~/.upstage-mcp-server/outputs/document_parsing/`
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`~/.mcp-server-upstage/outputs/document_parsing/`
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- **Information Extraction Results:**
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`~/.upstage-mcp-server/outputs/information_extraction/`
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`~/.mcp-server-upstage/outputs/information_extraction/`
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- **Generated Schemas:**
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`~/.upstage-mcp-server/outputs/information_extraction/schemas/`
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`~/.mcp-server-upstage/outputs/information_extraction/schemas/`
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## Local/Development Setup
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### Step 1: Clone the Repository
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```bash
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git clone https://github.com/UpstageAI/upstage-mcp-server.git
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cd upstage-mcp-server
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git clone https://github.com/UpstageAI/mcp-server-upstage.git
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cd mcp-server-upstage
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```
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### Step 2: Set Up the Python Environment
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```json
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{
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"mcpServers": {
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"upstage-mcp-server": {
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"mcp-server-upstage": {
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"command": "uv",
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"args": [
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"run",
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"--directory",
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"C:\\path\\to\\cloned\\upstage-mcp-server",
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"C:\\path\\to\\cloned\\mcp-server-upstage",
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"python",
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"-m",
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"upstage_mcp.server"
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}
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}
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```
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Replace `C:\\path\\to\\cloned\\upstage-mcp-server` with your actual repository path.
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Replace `C:\\path\\to\\cloned\\mcp-server-upstage` with your actual repository path.
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**For macOS/Linux:**
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```json
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{
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"mcpServers": {
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"upstage-mcp-server": {
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"mcp-server-upstage": {
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"command": "/Users/username/.local/bin/uv",
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"args": [
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"run",
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"--directory",
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"/path/to/cloned/upstage-mcp-server",
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"/path/to/cloned/mcp-server-upstage",
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"python",
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"-m",
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"upstage_mcp.server"
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```
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Replace:
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- `/Users/username/.local/bin/uv` with the output of `which uv`.
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- `/path/to/cloned/upstage-mcp-server` with the absolute path to your local clone.
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- `/path/to/cloned/mcp-server-upstage` with the absolute path to your local clone.
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> **Tip for macOS/Linux users:** If connection issues occur, using the full path to your uv executable can improve reliability.
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- **Server Not Starting:**
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Verify that your virtual environment is activated and all dependencies are installed. Additionally, review the Claude Desktop log files for errors:
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- **Windows:** `%APPDATA%\Claude\logs\mcp-server-upstage-mcp-server.log`
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- **macOS:** `~/Library/Logs/Claude/mcp-server-upstage-mcp-server.log`
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- **Windows:** `%APPDATA%\Claude\logs\mcp-server-mcp-server-upstage.log`
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- **macOS:** `~/Library/Logs/Claude/mcp-server-mcp-server-upstage.log`
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- **Server Connection Issues:**
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Restart Claude Desktop. Ensure that `uvx` is installed and available in your system PATH, or use its absolute path in your configuration if needed.
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For troubleshooting, view the server logs at:
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- **Windows:**
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`%APPDATA%\Claude\logs\mcp-server-upstage-mcp-server.log`
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`%APPDATA%\Claude\logs\mcp-server-mcp-server-upstage.log`
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- **macOS:**
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`~/Library/Logs/Claude/mcp-server-upstage-mcp-server.log`
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`~/Library/Logs/Claude/mcp-server-mcp-server-upstage.log`
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## Contributing
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examples/README.md

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- Python 3.10+
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- Upstage API Key (get from [Upstage Console](https://console.upstage.ai/api-keys))
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- OpenAI API Key (for both examples)
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- The Upstage MCP Server package (`upstage-mcp-server`)
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- The Upstage MCP Server package (`mcp-server-upstage`)
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## Getting Started
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1. Install the Upstage MCP Server:
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```
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uv pip install upstage-mcp-server
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uv pip install mcp-server-upstage
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```
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2. Set up your environment variables:
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export OPENAI_API_KEY="your-openai-api-key"
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```
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3. Choose an example directory and follow the README instructions there to run the example.
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3. Choose an example directory and follow the README instructions there to run the example.

examples/langchain/README.md

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- Python 3.10+
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- Upstage API Key (for both the MCP Server and Solar model)
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- The following Python packages:
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- `upstage-mcp-server`
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- `mcp-server-upstage`
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- `langchain-mcp-adapters`
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- `langchain-upstage`
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- `langchain`
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1. Install the required packages:
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```
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uv pip install upstage-mcp-server langchain-mcp-adapters langchain-upstage langchain uvx
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uv pip install mcp-server-upstage langchain-mcp-adapters langchain-upstage langchain uvx
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```
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2. Set up your environment variable:

examples/langchain/langchain_main.py

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# Set up parameters for the MCP server
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server_params = StdioServerParameters(
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command="uvx",
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args=["upstage-mcp-server"],
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args=["mcp-server-upstage"],
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env={
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"UPSTAGE_API_KEY": upstage_api_key
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}

examples/openai_agent/README.md

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- Upstage API Key
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- OpenAI API Key
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- The following Python packages:
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- `upstage-mcp-server`
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- `mcp-server-upstage`
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- `openai`
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- `openai-agents`
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- `uvx`
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1. Install the required packages:
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```
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uv pip install upstage-mcp-server openai openai-agents uvx
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uv pip install mcp-server-upstage openai openai-agents uvx
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```
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2. Set up your environment variables:

examples/openai_agent/openai_main.py

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cache_tools_list=True, # Cache the tools list for better performance
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params={
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"command": "uvx",
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"args": ["upstage-mcp-server"],
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"args": ["mcp-server-upstage"],
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"env": {
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"UPSTAGE_API_KEY": upstage_api_key,
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}

pyproject.toml

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build-backend = "hatchling.build"
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[project]
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name = "upstage-mcp-server"
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name = "mcp-server-upstage"
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dynamic = ["version"]
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description = "An MCP server for Upstage document parsing and information extraction"
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readme = "README.md"
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]
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[project.urls]
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Homepage = "https://github.com/UpstageAI/upstage-mcp-server"
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Issues = "https://github.com/UpstageAI/upstage-mcp-server/issues"
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Repository = "https://github.com/UpstageAI/upstage-mcp-server"
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Homepage = "https://github.com/UpstageAI/mcp-server-upstage"
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Issues = "https://github.com/UpstageAI/mcp-server-upstage/issues"
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Repository = "https://github.com/UpstageAI/mcp-server-upstage"
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[project.scripts]
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upstage-mcp-server = "upstage_mcp.server:main"
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mcp-server-upstage = "upstage_mcp.server:main"
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[tool.hatch.version]
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path = "src/upstage_mcp/__init__.py"

src/upstage_mcp/document_parser.py

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# Setup output directories
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def setup_output_directories() -> tuple:
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"""Set up output directories for document parsing results."""
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output_dir = Path.home() / ".upstage-mcp-server" / "outputs"
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output_dir = Path.home() / ".mcp-server-upstage" / "outputs"
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doc_parsing_dir = output_dir / "document_parsing"
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os.makedirs(doc_parsing_dir, exist_ok=True)

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