# Extracta.ai — MCP server on mcp.ai
> Connect your Extracta.ai account and use 10 tools for document data extraction straight from your AI agent. Connect with your own API key. Extracta.ai is an AI-powered platform that automates data extraction from various document types, including PDFs, images, and text files, without requiring prior training.

By: mcp.ai · official
Page: https://mcp.ai/extracta_ai

## Connect (MCP protocol)
Remote MCP endpoint (HTTP, streamable): https://api.mcp.ai/p_extracta_ai?ms=1787293560000
Add it as a custom/remote MCP connector, then authenticate when prompted.

## REST API (no MCP client required)
Every tool is also a REST endpoint, authed with a workspace API key.
Discover: GET https://api.mcp.ai/api/extracta_ai/_endpoints   # public; lists every endpoint
Call:     POST https://api.mcp.ai/api/extracta_ai/<endpoint>
  Authorization: Bearer sk_live_…   # create one at https://mcp.ai/settings/api-keys
  Content-Type: application/json
  Body: { …args }   →   { "ok": true, "tool": "<id>", "result": { … } }

## Developer docs
How to use (MCP or REST), markdown: https://mcp.ai/extracta_ai/skill.md
Postman collection (v2.1): https://mcp.ai/extracta_ai/postman.json

## Tools
- extracta_ai_create_classification(classificationDetails: object) — Creates a new document classification configuration. Define a list of possible document types with their characteristics (name, description, unique words). Returns a classification ID that can be used
- extracta_ai_create_extraction(extractionDetails: object) — Creates a new extraction configuration for processing documents. Define what fields to extract (e.g., names, dates, amounts) and processing options. Returns an extraction ID that can be used to upload
- extracta_ai_delete_classification(classificationId: string) — Permanently deletes an entire document classification process including all associated batches, results, and uploaded files. Use this when you want to remove a classification that is no longer needed.
- extracta_ai_delete_extraction(extractionId: string) — Permanently deletes an extraction job and its configuration from the system. Use this when you want to remove an extraction job that is no longer needed. This action is idempotent - calling it multipl
- extracta_ai_get_batch_results(batchId: string, extractionId: string) — Retrieves extraction results for a specific batch of documents. Returns the extracted data for each file in the batch, along with processing status and file information. If the batch is still processi
- extracta_ai_get_credits() — Retrieves the current credit balance available on the account. The system operates on a per-page consumption model where 1 credit = 1 page of document processing. Use this action to check remaining cr
- extracta_ai_update_classification(classificationId: string, classificationDetails: object) — Updates an existing document classification by modifying its parameters. Use this to change the classification name, description, or document types (including their keywords and linked extractions). R
- extracta_ai_update_extraction(extractionId: string, extractionDetails: object) — Updates an existing document extraction process by modifying specified parameters. Only fields provided in the request are modified; omitted fields remain unchanged. Use this to change the extraction'
- extracta_ai_view_classification(classificationId: string) — Retrieves details of an existing classification configuration including name, description, document types, associated keywords, and linked extraction templates. Use this action to verify classificatio
- extracta_ai_view_extraction(extractionId: string) — Retrieves detailed configuration and status information for an existing extraction job. Returns the extraction's name, description, language, configured fields, processing options, and any associated 

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

## Links
Docs: https://mcp.ai/docs/mcps/extracta_ai
Website: https://mcp.ai/mcps/extracta_ai