How to connect Nano nets to Claude Cowork

Cowork is Anthropic's AI agent for knowledge work. Think of it as Claude Code for everything else. It works autonomously with your computer, local files, and applications to accomplish complex tasks.

This guide walks you through the easiest and most secure way to connect your Nano nets account to Cowork via Composio Connect, enabling it to extract table data from recent invoices, upload new receipts for OCR model training, list all documents processed by a workflow, and more such actions on your behalf without compromising your account security.

Connecting Nano nets to Claude Cowork

1. Open Customize

In Claude Desktop, click Customize in the left sidebar, then select Connectors and click the + icon at the top.

2. Add the Composio MCP server

Click Add custom connector and paste in the Composio MCP server URL:

Claude Cowork is Anthropic's agent for general knowledge work. It can use your computer, files, and connected applications to complete longer-running tasks across your work tools.

With Composio Connect, Cowork can securely access apps like Nano nets through MCP without you sharing account credentials directly with the agent.

The Nano nets MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Nano nets account. It provides structured and secure access to your intelligent document processing tools, so your agent can create, manage, and train OCR models, extract data from documents, and automate document workflows on your behalf.

• Automated document data extraction: Let your agent process unstructured documents and pull out structured data using Nano nets' powerful AI-driven OCR models.
• OCR model management: Easily create, update, and delete OCR models, allowing your agent to adjust to changing document types and business needs.
• Workflow and document handling: Enable your agent to list, track, and manage documents within workflows, so you can monitor processing status and outcomes efficiently.
• Training image uploads and model improvement: Have your agent upload new training images to OCR models, continually improving accuracy and adapting to new document formats.
• Comprehensive model insights: Retrieve detailed information about your OCR models and their prediction files, empowering your agent to audit, debug, or optimize model performance as needed.