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AparaviSoftware Mcp Server

mcp-aparavisoftware-mcp-server · by AparaviSoftware

This is the official Aparavi MCP Server

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$ agentstack add mcp-aparavisoftware-mcp-server

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Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Aparavi MCP Server

An MCP (Model Context Protocol) server that integrates with Aparavi's document processing capabilities. This server allows Language Models to process documents through Aparavi's API and receive cleaned text output.

[](https://www.npmjs.com/package/aparavi-mcp) [](https://opensource.org/licenses/MIT)

Features

  • 📄 Document processing via Aparavi API
  • 🧹 Clean text extraction without metadata
  • 🔌 MCP-compliant interface
  • ⚙️ Environment-based configuration
  • 🚀 Async processing support
  • 📦 Easy installation via NPX
  • 🔍 OCR capabilities for system diagrams
  • 🐍 Python-based with Node.js wrapper

Table of Contents

  • [Prerequisites](#prerequisites)
  • [Quick Start](#quick-start)
  • [Installation](#installation)
  • [For Users](#for-users)
  • [For Developers](#for-developers)
  • [Configuration](#configuration)
  • [Usage](#usage)
  • [Running as a User](#running-as-a-user)
  • [Running for Development](#running-for-development)
  • [API Documentation](#api-documentation)
  • [Testing](#testing)
  • [Project Structure](#project-structure)
  • [Contributing](#contributing)

Prerequisites

  • Python 3.8 or higher
  • Node.js 14 or higher
  • Git (for development setup)

Installation

For Users

There are two ways to install the MCP server as a user:

  1. Get your API Key:

For EU Users https://dtc.aparavi.eu/usage or US Users https://dtc.aparavi.com/usage

  1. Run the Server

```bash

# Choose which Aparavi server you want to use and set API keys in terminal

# For US users: # Get Aparavi API Key from: https://dtc.aparavi.com/ # Set APARAVIAPIURL to: https://eaas.aparavi.com

# For EU users: # Get Aparavi API Key from: https://dtc.aparavi.eu/ # Set APARAVIAPIURL to: https://eaas.aparavi.eu

# For Unix/Linux/macOS export APARAVIAPIKEY=yourapikeyhere export APARAVIAPIURL=yoururl_here

# For Windows - Set API keys in Command Prompt set APARAVIAPIKEY=yourapikeyhere set APARAVIAPIURL="yoururl_here"

# OR for Windows PowerShell $env:APARAVIAPIKEY="yourapikeyhere" $env:APARAVIAPIURL="yoururl_here"

# Run the server (same command for all platforms) npx aparavi-mcp@latest ```

  1. Add Server to your Client

Update your MCP_config.json file in the client with this: ```json { "mcpServers": { "aparavi": { "serverUrl": "http://localhost:8000/mcp" } } }

```

For Developers

For local development and testing:

  1. Clone the Repository

``bash git clone https://github.com/AparaviSoftware/mcp-server cd mcp-server ``

  1. Set Environment Variables

```bash # For US users: https://eaas.aparavi.com # For EU users: https://eaas.aparavi.eu

# For Unix/Linux/macOS export APARAVIAPIKEY=yourapikeyhere export APARAVIAPIURL=yoururl_here

# For Windows - Set API keys in Command Prompt set APARAVIAPIKEY=yourapikeyhere set APARAVIAPIURL="yoururl_here"

# OR for Windows PowerShell $env:APARAVIAPIKEY="yourapikeyhere" $env:APARAVIAPIURL="yoururl_here" ```

  1. Set Up Python Environment

``bash npx aparavi-mcp@latest ``

  1. Running Tests

First, ensure your server is running (from step 1). Then you can run and configure tests:

``bash # Run the test tool python tests/test_tool.py ``

To test different tools or files, open tests/test_tool.py and modify the main() function: ```python def main(): # Change the file path to test different documents filepath = "tests/testdata/testdocument.txt" # Or try other test files: # filepath = "tests/testdata/SDDRoadTrip.pdf" # filepath = "tests/testdata/systemdiagram.jpeg"

# Change the tool name to test different tools toolname = "documentprocessor" # Available tools: # - "AparaviDocumentProcessor" (for text documents) # - "AdvancedOCRParser" (for diagrams/images)

runtooltest(filepath, toolname) ```

Configuration

Required Environment Variables

  • APARAVI_API_KEY: Your Aparavi API key (required)
  • APARAVI_API_URL: Your Aparavi API server (required)

Optional Environment Variables

  • VISION_API_KEY: Your Mistral Vision API key (required only for video processing tool)
  • Only needed if you want to use the Aparavi_Video_Processor tool
  • Get your API key from Mistral AI
  • Set it the same way as other environment variables:

```bash # Unix/Linux/macOS export VISIONAPIKEY=yourmistralapikeyhere

# Windows Command Prompt set VISIONAPIKEY=yourmistralapikeyhere

# Windows PowerShell $env:VISIONAPIKEY="yourmistralapikeyhere" ```

Project Structure

aparavi-mcp/
├── bin/                    # Executable scripts
│   ├── index.js           # Node.js entry point
│   └── setup.sh           # Python environment setup
|__ prompts/               #Preconfigured prompts
├── tools/                 # MCP tool implementations
├── resources/             # Configuration and resources
├── tests/                 # Test files
├── mcp-server.py         # Main Python server
├── requirements.txt      # Python dependencies
└── package.json         # Node.js package config

License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.