# LLMWhisperer

```json
{
  "name": "LLMWhisperer",
  "slug": "llmwhisperer",
  "url": "https://composio.dev/toolkits/llmwhisperer",
  "markdown_url": "https://composio.dev/toolkits/llmwhisperer.md",
  "logo_url": "https://logos.composio.dev/api/llmwhisperer",
  "categories": [
    "ai & machine learning",
    "document & file management",
    "productivity & project management"
  ],
  "is_composio_managed": false,
  "updated_at": "2026-03-29T06:40:48.248Z"
}
```

![LLMWhisperer logo](https://logos.composio.dev/api/llmwhisperer)

## Description

Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with LLMWhisperer MCP or direct API to extract structured data, summarize complex documents, classify content, and label information through natural language.

## Summary

LLMWhisperer makes complex document data accessible to language models. It helps LLMs accurately interpret and process structured information.

## Categories

- ai & machine learning
- document & file management
- productivity & project management

## Toolkit Details

- Tools: 10

## Images

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

## Authentication

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

## Suggested Prompts

- Summarize main points from uploaded contract
- Extract key dates from legal document
- Classify sections of this technical report

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `LLMWHISPERER_USAGE_GET_INFO` | Get Usage Information | Tool to check usage metrics of your LLMWhisperer account. Use when you need to monitor API consumption, verify quotas, or check remaining page limits. |
| `LLMWHISPERER_USAGE_GET_STATS` | Get Usage Statistics | Tool to retrieve usage statistics for your LLMWhisperer account based on a specific tag. Use when you need to check consumption metrics for a given tag and optional date range. Returns usage data for the preceding 30 days when date parameters are omitted. |
| `LLMWHISPERER_WEBHOOK_DELETE` | Delete Webhook | Tool to delete a registered webhook from LLMWhisperer system. Use when you need to remove a webhook that is no longer needed. |
| `LLMWHISPERER_WEBHOOK_GET_DETAILS` | Get Webhook Details | Tool to retrieve registered webhook details for LLMWhisperer. Use when you need to get the configuration of a specific webhook including its URL and authentication token. |
| `LLMWHISPERER_REGISTER_WEBHOOK` | Register Webhook | Tool to register a new webhook endpoint for LLMWhisperer async notifications. Use when you need to set up a callback URL to receive processing results. During registration, a test payload is sent to verify the webhook endpoint is functioning and returns HTTP 200. |
| `LLMWHISPERER_UPDATE_WEBHOOK_CONFIGURATION` | Update Webhook Configuration | Tool to update an existing webhook configuration for document conversion callbacks. Use when you need to modify the callback URL, authentication token, or webhook identifier. The system validates the webhook by sending a test payload and requires a 200 status response. |
| `LLMWHISPERER_CHECK_WHISPER_STATUS` | Check Whisper Status | Tool to check the status of a text extraction process in LLMWhisperer. Use when the conversion is done in async mode to poll for completion status. |
| `LLMWHISPERER_CONVERT_DOCUMENT_TO_TEXT` | Convert Document to Text | Tool to convert PDFs and scanned documents into LLM-optimized text format asynchronously. Use when you need to extract text from documents for LLM processing. After submission, use the returned whisper_hash to poll status and retrieve converted text. Either document_url (with url_in_post=true) or document_content must be provided. |
| `LLMWHISPERER_GET_WHISPER_DETAIL` | Get Whisper Detail | Tool to retrieve comprehensive details about ongoing or completed text extraction process. Use when you need to monitor the status and progress metrics of a text extraction job. |
| `LLMWHISPERER_RETRIEVE_WHISPER_TEXT` | Retrieve Whisper Text | Tool to retrieve extracted text from asynchronous whisper processing. Use when the conversion process was initiated in async mode and you need to retrieve the results using the whisper_hash identifier. Note that retrieval is single-use for security - once retrieved, the same whisper_hash cannot be used again. |

## 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 LLMWhisperer Tools via Tool Router with Your Agent

Get tools from Tool Router session and execute LLMWhisperer actions with your Agent
```python
tools = session.tools
response = openai.responses.create(
  model='gpt-4.1',
  tools=tools,
  input=[{
    'role': 'user',
    'content': 'Extract key facts from the attached contract document.'
  }]
)
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 key facts from the attached contract document.'
  }],
});
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 for Python or TypeScript
```python
pip install composio claude-agent-sdk
```

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

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

Import and initialize the Composio client, then create a Tool Router session for LLMWhisperer
```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' });
const session = await composio.create('your-user-id');
console.log(`Tool Router session created: ${session.mcp.url}`);
```

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

Use the MCP server with your AI agent (Anthropic Claude or Mastra)
```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 LLMWhisperer tools.',
    max_turns=10
)

async def main():
    async with ClaudeSDKClient(options=options) as client:
        await client.query('Summarize all compliance sections in the uploaded financial report.')
        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 } from 'ai';

const client = await createMCPClient({
  transport: {
    type: 'http',
    url: session.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: 'Summarize all compliance sections in the uploaded financial report.'
  }],
  maxSteps: 5,
});

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

## Why Use Composio?

### 1. AI Native LLMWhisperer Integration

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

### 2. Managed Auth

- Built-in OAuth handling with automatic token refresh and rotation
- Central place to manage, scope, and revoke LLMWhisperer 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 LLMWhisperer
- Scoped, least privilege access to LLMWhisperer resources
- Full audit trail of agent actions to support review and compliance

## Use LLMWhisperer with any AI Agent Framework

Choose a framework you want to connect LLMWhisperer with:

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

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## Frequently Asked Questions

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

Yes, LLMWhisperer 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)