by cognitive-stack
Automate document workflows with Orion Vision and Azure Form Recognizer for intelligent document processing and assembly
Extracts structured data from documents like receipts, invoices, and ID cards using Azure Form Recognizer. Automates document processing by converting images and PDFs into structured data.
Orion Vision (Azure Form Recognizer) is a community-built MCP server published by cognitive-stack that provides AI assistants with tools and capabilities via the Model Context Protocol. Automate document workflows with Orion Vision and Azure Form Recognizer for intelligent document processing and assembly It is categorized under ai ml.
You can install Orion Vision (Azure Form Recognizer) in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
Orion Vision (Azure Form Recognizer) is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
Strong directory entry: Orion Vision (Azure Form Recognizer) surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Orion Vision (Azure Form Recognizer) is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Orion Vision (Azure Form Recognizer) has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Orion Vision (Azure Form Recognizer) is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Orion Vision (Azure Form Recognizer) is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Orion Vision (Azure Form Recognizer) reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Orion Vision (Azure Form Recognizer) has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
We wired Orion Vision (Azure Form Recognizer) into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Orion Vision (Azure Form Recognizer) is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
I recommend Orion Vision (Azure Form Recognizer) for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
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🔌 Compatible with Cline, Cursor, Claude Desktop, and any other MCP Clients!
Orion Vision MCP is also compatible with any MCP client
The Model Context Protocol (MCP) is an open standard that enables AI systems to interact seamlessly with various data sources and tools, facilitating secure, two-way connections.
The Orion Vision MCP server provides:
Before you begin, ensure you have:
npx -y orion-vision-mcp@latest
To install Orion Vision MCP Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @orion-vision/mcp --client claude
The easiest way to set up the Orion Vision MCP server in Cline is through the marketplace with a single click:
Alternatively, you can manually set up the Orion Vision MCP server in Cline:
# For macOS:
code ~/Library/Application\ Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json
# For Windows:
code %APPDATA%\Code\User\globalStorage\saoudrizwan.claude-dev\settings\cline_mcp_settings.json
{
"mcpServers": {
"orion-vision-mcp": {
"command": "npx",
"args": ["-y", "orion-vision-mcp@latest"],
"env": {
"AZURE_FORM_RECOGNIZER_ENDPOINT": "your-endpoint-here",
"AZURE_FORM_RECOGNIZER_KEY": "your-key-here"
},
"disabled": false,
"autoApprove": []
}
}
}
Note: Requires Cursor version 0.45.6 or higher
To set up the Orion Vision MCP server in Cursor:
env AZURE_FORM_RECOGNIZER_ENDPOINT=your-endpoint AZURE_FORM_RECOGNIZER_KEY=your-key npx -y orion-vision-mcp@latest
Important: Replace
your-endpointandyour-keywith your Azure Form Recognizer credentials
# Create the config file if it doesn't exist
touch "$HOME/Library/Application Support/Claude/claude_desktop_config.json"
# Opens the config file in TextEdit
open -e "$HOME/Library/Application Support/Claude/claude_desktop_config.json"
code %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"orion-vision-mcp": {
"command": "npx",
"args": ["-y", "orion-vision-mcp@latest"],
"env": {
"AZURE_FORM_RECOGNIZER_ENDPOINT": "your-endpoint-here",
"AZURE_FORM_RECOGNIZER_KEY": "your-key-here"
}
}
}
}
Once the installation is complete, and the Claude desktop app is configured, you must completely close and re-open the Claude desktop app to see the orion-vision-mcp server. You should see a hammer icon in the bottom left of the app, indicating available MCP tools.
Analyze the document at "https://example.com/document.pdf" using Azure Form Recognizer.
Extract data from the invoice at "https://example.com/invoice.pdf".
Process the ID document at "https://example.com/id.pdf" and extract relevant information.
Server Not Found
npm --versionnode --versionAzure Form Recognizer Credentials Issues
Document Processing Issues
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.