# Nano nets

```json
{
  "name": "Nano nets",
  "slug": "nano_nets",
  "url": "https://composio.dev/toolkits/nano_nets",
  "markdown_url": "https://composio.dev/toolkits/nano_nets.md",
  "logo_url": "https://logos.composio.dev/api/nano_nets",
  "categories": [
    "document & file management"
  ],
  "is_composio_managed": false,
  "updated_at": "2026-05-12T10:19:46.789Z"
}
```

![Nano nets logo](https://logos.composio.dev/api/nano_nets)

## Description

Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with Nano nets MCP or direct API to extract key data, process invoices, classify documents, and automate workflows through natural language.

## Summary

Nano nets is an AI-powered Intelligent Document Processing API for extracting structured data from unstructured documents. It boosts workflow automation by turning messy documents into clean, usable information.

## Categories

- document & file management

## Toolkit Details

- Tools: 11

## Images

- Logo: https://logos.composio.dev/api/nano_nets

## Authentication

- **Api Key**
  - Type: `api_key`
  - Description: Api Key authentication for Nanonets.
  - Setup:
    - Configure Api Key credentials for Nanonets.
    - Use the credentials when creating an auth config in Composio.

## Suggested Prompts

- Extract table data from recent invoices
- Upload new receipts for OCR model training
- List all documents processed by a workflow
- Get metadata for a specific OCR model

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `NANO_NETS_CREATE_MODEL` | Create Model | Tool to create a new image classification or OCR model. Use when you need to initialize a model before uploading training images. Provide a list of categories/classes that the model should learn to identify or extract. |
| `NANO_NETS_DELETE_MODEL` | Delete OCR Model | Permanently deletes an OCR model from Nanonets. Use this action when you need to remove a trained model that is no longer needed. This action is irreversible - once deleted, the model and all its training data cannot be recovered. Prerequisites: Obtain the model_id from the 'Get all OCR models' action first. |
| `NANO_NETS_GET_ALL_MODELS` | Get All Models | Retrieves all models (OCR and Image Classification) in the user's NanoNets account. Returns model details including ID, type, status, accuracy, and extractable fields/categories. Use to discover available models before performing predictions or training operations. |
| `NANO_NETS_GET_ALL_PREDICTION_FILES` | Get All Prediction Files | Retrieve all prediction files (OCR results) for a NanoNets model. Use this tool to: - List all documents/images that have been processed by an OCR model - Get prediction results including extracted text and field values - Access file URLs and processing status for each prediction The response includes prediction labels with extracted text, confidence scores, and bounding box coordinates for each processed file. |
| `NANO_NETS_GET_MODEL_DETAILS` | Get OCR Model Details | Tool to retrieve details of an OCR model. Use when you need full metadata of a model by its ID. |
| `NANO_NETS_GET_TRAINING_IMAGES` | Get OCR Training Images | Tool to retrieve training images for an OCR model. Use when you need to page through images associated with a model before training or analysis. |
| `NANO_NETS_GET_WORKFLOWS` | Get Workflows | Tool to retrieve a list of all workflows in your Nanonets account. Use when you need to inventory or inspect all configured workflows. |
| `NANO_NETS_LIST_DOCUMENTS` | List Workflow Documents | Retrieve a paginated list of documents processed by a NanoNets workflow. Returns document metadata including processing status, upload timestamp, verification status, and page details. Use this to monitor document processing progress or access extracted data from previously uploaded documents. |
| `NANO_NETS_UPDATE_MODEL` | Update Model AI Guidelines | Update AI Agent guidelines for an OCR model. Sets instructions for how the AI should handle field and table predictions. Only works for Instant Learning models. Use this to customize extraction behavior for specific document types. |
| `NANO_NETS_UPLOAD_TRAINING_IMAGES_BY_FILE` | Upload Training Images by File | Tool to upload a training image file to a specified OCR model. Use when adding a local image file to train the model. Supported file formats include PNG, JPEG, and PDF. |
| `NANO_NETS_UPLOAD_TRAINING_IMAGES_BY_URL` | Upload Training Images by URL | Tool to upload training images by URL to a specified OCR model. Use when adding URLs of images to a model for training purposes. |

## Supported Triggers

None listed.

## Installation and MCP Setup

### Path 1: SDK Installation

#### Path 1, Step 1: Install Composio

Install the Composio SDK
```python
pip install composio_openai
```

```typescript
npm install @composio/openai
```

#### Path 1, Step 2: Initialize Composio and Create Tool Router Session

Import and initialize Composio client, then create a Tool Router session
```python
from openai import OpenAI
from composio import Composio
from composio_openai import OpenAIResponsesProvider

composio = Composio(provider=OpenAIResponsesProvider())
openai = OpenAI()
session = composio.create(user_id='your-user-id')
```

```typescript
import OpenAI from 'openai';
import { Composio } from '@composio/core';
import { OpenAIResponsesProvider } from '@composio/openai';

const composio = new Composio({
  provider: new OpenAIResponsesProvider(),
});
const openai = new OpenAI({});
const session = await composio.create('your-user-id');
```

#### Path 1, Step 3: Execute Nano nets Tools via Tool Router with Your Agent

Get tools from Tool Router session and execute Nano nets actions with your Agent
```python
tools = session.tools
response = openai.responses.create(
  model='gpt-4.1',
  tools=tools,
  input=[{
    'role': 'user',
    'content': 'Extract structured data from recent invoices uploaded this week using Nano nets.'
  }]
)
result = composio.provider.handle_tool_calls(
  response=response,
  user_id='your-user-id'
)
print(result)
```

```typescript
const tools = session.tools;
const response = await openai.responses.create({
  model: 'gpt-4.1',
  tools: tools,
  input: [{
    role: 'user',
    content: 'Extract structured data from recent invoices uploaded this week using Nano nets.'
  }],
});
const result = await composio.provider.handleToolCalls(
  'your-user-id',
  response.output
);
console.log(result);
```

### Path 2: MCP Server Setup

#### Path 2, Step 1: Install Composio

Install the Composio SDK and Claude Agent SDK
```python
pip install composio claude-agent-sdk
```

```typescript
npm install @composio/core ai @ai-sdk/openai @ai-sdk/mcp
```

#### Path 2, Step 2: Create Tool Router Session

Initialize the Composio client and create a Tool Router session
```python
from composio import Composio
from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions

composio = Composio(api_key='your-composio-api-key')
session = composio.create(user_id='your-user-id')
url = session.mcp.url
```

```typescript
import { Composio } from '@composio/core';

const composio = new Composio({ apiKey: 'your-api-key' });

console.log("Creating Tool Router session...");
const { mcp } = await composio.create('your-user-id');
console.log(`Tool Router session created: ${mcp.url}`);
```

#### Path 2, Step 3: Connect to AI Agent

Use the MCP server with your AI agent
```python
import asyncio

options = ClaudeAgentOptions(
    permission_mode='bypassPermissions',
    mcp_servers={
        'tool_router': {
            'type': 'http',
            'url': url,
            'headers': {
                'x-api-key': 'your-composio-api-key'
            }
        }
    },
    system_prompt='You are a helpful assistant with access to Nano nets tools.',
    max_turns=10
)

async def main():
    async with ClaudeSDKClient(options=options) as client:
        await client.query('Extract fields from this invoice PDF')
        async for message in client.receive_response():
            if hasattr(message, 'content'):
                for block in message.content:
                    if hasattr(block, 'text'):
                        print(block.text)

asyncio.run(main())
```

```typescript
import { openai } from '@ai-sdk/openai';
import { experimental_createMCPClient as createMCPClient } from '@ai-sdk/mcp';
import { generateText, stepCountIs } from 'ai';

const client = await createMCPClient({
  transport: {
    type: 'http',
    url: mcp.url,
    headers: { 'x-api-key': 'your-composio-api-key' }
  }
});

const tools = await client.tools();

const { text } = await generateText({
  model: openai('gpt-4o'),
  tools,
  messages: [{ role: 'user', content: 'Extract fields from this invoice PDF' }],
  stopWhen: stepCountIs( 5 )
});

console.log(`Agent: ${text}`);
```

## Why Use Composio?

### 1. AI Native Nano nets Integration

- Supports both Nano nets MCP and direct API based integrations
- Structured, LLM-friendly schemas for reliable tool execution
- Rich coverage for reading, writing, and querying your Nano nets data

### 2. Managed Auth

- Built-in API Key handling with secure storage
- Central place to manage, scope, and revoke Nano nets access
- Per user and per environment credentials instead of hard-coded keys

### 3. Agent Optimized Design

- Tools are tuned using real error and success rates to improve reliability over time
- Comprehensive execution logs so you always know what ran, when, and on whose behalf

### 4. Enterprise Grade Security

- Fine-grained RBAC so you control which agents and users can access Nano nets
- Scoped, least privilege access to Nano nets resources
- Full audit trail of agent actions to support review and compliance

## Use Nano nets with any AI Agent Framework

Choose a framework you want to connect Nano nets with:

- [OpenAI Agents SDK](https://composio.dev/toolkits/nano_nets/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/nano_nets/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/nano_nets/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/nano_nets/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/nano_nets/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/nano_nets/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/nano_nets/framework/hermes-agent)
- [Google ADK](https://composio.dev/toolkits/nano_nets/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/nano_nets/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/nano_nets/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/nano_nets/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/nano_nets/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/nano_nets/framework/crew-ai)
- [Pydantic AI](https://composio.dev/toolkits/nano_nets/framework/pydantic-ai)
- [AutoGen](https://composio.dev/toolkits/nano_nets/framework/autogen)

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## Frequently Asked Questions

### Do I need my own developer credentials to use Nano nets with Composio?

Yes, Nano nets requires you to configure your own API key credentials. Once set up, Composio handles secure credential storage and API request handling for you.

### Can I use multiple toolkits together?

Yes! Composio's Tool Router enables agents to use multiple toolkits. [Learn more](https://docs.composio.dev/tool-router/overview).

### Is Composio secure?

Composio is SOC 2 and ISO 27001 compliant with all data encrypted in transit and at rest. [Learn more](https://trust.composio.dev).

### What if the API changes?

Composio maintains and updates all toolkit integrations automatically, so your agents always work with the latest API versions.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)