LLMWhisperer MCP server for AI agents and assistants

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.

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Api Key

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

10 Tools

Try LLMWhisperer now

Type what you want done — sign in and watch it run live in the Tool Router playground.

TOOL ROUTER PLAYGROUND
LLMWhisperer
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TOOLS

Supported Tools

Every LLMWhisperer action and event your agent gets out of the box.

Get Usage Information

Tool to check usage metrics of your LLMWhisperer account.

Get Usage Statistics

Tool to retrieve usage statistics for your LLMWhisperer account based on a specific tag.

Delete Webhook

Tool to delete a registered webhook from LLMWhisperer system.

Get Webhook Details

Tool to retrieve registered webhook details for LLMWhisperer.

Register Webhook

Tool to register a new webhook endpoint for LLMWhisperer async notifications.

Update Webhook Configuration

Tool to update an existing webhook configuration for document conversion callbacks.

Check Whisper Status

Tool to check the status of a text extraction process in LLMWhisperer.

Convert Document to Text

Tool to convert PDFs and scanned documents into LLM-optimized text format asynchronously.

Get Whisper Detail

Tool to retrieve comprehensive details about ongoing or completed text extraction process.

Retrieve Whisper Text

Tool to retrieve extracted text from asynchronous whisper processing.

SETUP GUIDE

Connect LLMWhisperer MCP Tool with your Agent

1

Install Composio

typescript
npm install @composio/core ai @ai-sdk/openai @ai-sdk/mcp
Install the Composio SDK for Python or TypeScript
2

Initialize Client and Create Tool Router Session

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}`);
Import and initialize the Composio client, then create a Tool Router session for LLMWhisperer
3

Connect to AI Agent

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}`);
Use the MCP server with your AI agent (Anthropic Claude or Mastra)
SETUP GUIDE

Connect LLMWhisperer API Tool with your Agent

1

Install Composio

typescript
npm install @composio/openai
Install the Composio SDK
2

Initialize Composio and Create Tool Router Session

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');
Import and initialize Composio client, then create a Tool Router session
3

Execute LLMWhisperer Tools via Tool Router with Your Agent

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);
Get tools from Tool Router session and execute LLMWhisperer actions with your Agent

Why Use Composio?

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

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

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

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

Rolling this out across your team?

Give your team centralized access control across every framework with Composio’s MCP Gateway.

EXPLORE MCP GATEWAY
FAQ

Frequently asked questions

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.

Yes! Composio's Tool Router enables agents to use multiple toolkits. Learn more.

Yes. Composio is SOC 2 Type II compliant and is built to keep your LLMWhisperer connection and credentials secure. OAuth tokens and API keys are encrypted, and sensitive customer data is protected at rest and in transit.

Composio also undergoes independent security testing and continuously monitors its systems for security threats. You can review the latest reports and policies in the Composio Trust Center.

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

Create the key in your LLMWhisperer account settings, then paste it once on Composio's connection page. Composio stores it encrypted and uses it only for the LLMWhisperer actions your agent runs. Nobody else in your workspace can read it, and you can revoke it inside LLMWhisperer at any time.

When you connect a LLMWhisperer account through Composio, every action runs under that account, so anything the agent creates, sends, or changes shows up in LLMWhisperer as done by you. Keep an approval step in your prompt for actions with side effects, such as sending or deleting, and have the agent draft first.

Whatever the credentials you connect allow inside LLMWhisperer. If LLMWhisperer lets you scope a key to specific permissions, create a scoped one so the agent can only do what you intend. You can revoke the key inside LLMWhisperer at any time.

Yes. Composio supports multiple connected accounts for the same app, and that works in Claude, ChatGPT, or any other assistant you connect through Composio. Give each LLMWhisperer connection a name such as work or personal, and the assistant uses the one you mention in the request. Each account keeps its own credentials and nothing is merged.

The connection stops working the moment LLMWhisperer rejects the old key. Create a new key in LLMWhisperer and reconnect the account from the Composio dashboard or by asking your agent to reconnect LLMWhisperer. Nothing else changes.

Composio's free plan includes 100,000 tool calls per month with no credit card, which covers most personal LLMWhisperer use. Paid plans add higher limits and team features. Your LLMWhisperer plan and its API limits still apply as usual.

Built-in connectors usually give one AI access to a limited set of apps. Many people use Composio because it lets their AI connect to more apps than it normally supports, or connect to multiple accounts for the same app (e.g. connect Claude to multiple LLMWhisperer accounts).

With Composio, you connect LLMWhisperer once and then use it across different AI assistants without setting it up separately in each one. Connect your apps to Composio once, then connect Composio to whichever AI you use, whether that's Claude, ChatGPT, Hermes, or your own custom assistant.

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