# LLMWhisperer — how to use (mcp.ai)

Connect your LLMWhisperer account and use 11 tools for document data extraction straight from your AI agent. Connect with your own API key. LLMWhisperer is a technology that presents data from complex documents to LLMs in a way that they can best understand.

## Option A — via MCP (recommended)
Remote MCP endpoint (HTTP, streamable): `https://api.mcp.ai/p_llmwhisperer?ms=1787296140000`
Add it as a custom/remote MCP connector in your client (Claude, Cursor, VS Code…), then authenticate when prompted. Once connected, ask the agent to use the server's tools (e.g. `llmwhisperer_convert_document_to_text_v2`).

## Option B — via direct REST API
Base URL: `https://api.mcp.ai/api/llmwhisperer`
Auth: `Authorization: Bearer sk_live_…` — create a workspace API key at https://mcp.ai/settings/api-keys
Discover endpoints: `GET https://api.mcp.ai/api/llmwhisperer/_endpoints`

### Endpoints
- `POST https://api.mcp.ai/api/llmwhisperer/convert/document/to/text/v2` — Tool to convert PDF/scanned documents to text format for LLM consumption. Supports file upload or URL processing with multiple modes (native_text, low_cost, high_quality, form, table). Use when you ne
  - body: { tag?: string, url?: string, file?: object, lang?: string, mode?: string, filename?: string, output_mode?: string, url_in_post?: boolean, use_webhook?: string, add_line_nos?: boolean, page_seperator?: string, pages_to_extract?: string, webhook_metadata?: string, median_filter_size?: integer, mark_vertical_lines?: boolean, gaussian_blur_radius?: integer, mark_horizontal_lines?: boolean, line_splitter_strategy?: string, include_line_confidence?: boolean, line_splitter_tolerance?: number, horizontal_stretch_factor?: number }
- `POST https://api.mcp.ai/api/llmwhisperer/get/highlights` — Tool to get line metadata for highlighting extracted text in the original document. Returns bounding box coordinates (x, y, width, height) and page number for each line. Use when you need to create te
  - body: { lines?: string, whisper_hash: string, extract_all_lines?: boolean }
- `POST https://api.mcp.ai/api/llmwhisperer/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. The webhook URL is validated during registration
  - body: { url: string, auth_token?: string, webhook_name: string }
- `POST https://api.mcp.ai/api/llmwhisperer/usage/get/info` — Tool to check usage metrics of your LLMWhisperer account. Use when you need to monitor API consumption, verify quotas, or check remaining page limits.
- `POST https://api.mcp.ai/api/llmwhisperer/usage/get/stats` — 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 
  - body: { tag: string, to_date?: string, from_date?: string }
- `POST https://api.mcp.ai/api/llmwhisperer/webhook/delete` — Tool to delete a registered webhook from LLMWhisperer system. Use when you need to remove a webhook that is no longer needed.
  - body: { webhook_name: string }
- `POST https://api.mcp.ai/api/llmwhisperer/webhook/get/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.
  - body: { webhook_name: string }
- `POST https://api.mcp.ai/api/llmwhisperer/webhook/update` — 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 
  - body: { url: string, auth_token?: string, webhook_name: string }
- `POST https://api.mcp.ai/api/llmwhisperer/whisper/check/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.
  - body: { whisper_hash: string }
- `POST https://api.mcp.ai/api/llmwhisperer/whisper/get/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.
  - body: { whisper_hash: string }
- `POST https://api.mcp.ai/api/llmwhisperer/whisper/retrieve/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
  - body: { text_only?: boolean, whisper_hash: string }

## Example prompts
- "What can I do in LLMWhisperer?"
- "Show me a summary of my LLMWhisperer account"

## More
- Page: https://mcp.ai/llmwhisperer
- Agent spec (llms.txt): https://mcp.ai/llmwhisperer/llms.txt
- Postman collection: https://mcp.ai/llmwhisperer/postman.json