Extract text and structured fields from business documents with review and search.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "docintel-mcp" yet — see the docs or source repo.
Process this batch of invoices, extract full text plus structured fields such as invoice number, vendor name, date, and amount, and send low-confidence results to a human review queue.
Returns document text, structured field extractions, and a list of low-confidence items requiring human review.
Extract text and fields such as contract ID, parties, and effective date from these contracts; if any field has low confidence, automatically route it to a human review queue.
Outputs contract content and extracted fields, with uncertain fields listed separately for human review.
Search processed documents for records containing "purchase order" with amounts above a specified threshold, and return matching documents and extracted fields.
Returns a list of matching documents along with text and structured field data for reference.
Office or operations teams can use it to process invoices, contracts, and other business documents in bulk, automatically extracting text and key fields to reduce manual entry. Uncertain results can be sent to a human review workflow.
Data analysts or developers can centralize processed documents and search them by text content or extracted fields. This makes it easier to locate historical documents and reuse structured information.
When document quality varies or field formats are complex, teams can automatically send low-confidence extractions to a human review queue to balance speed and accuracy. This is useful for workflows that require careful handling of business documents.
It is a document intelligence MCP server that extracts text and structured fields from business documents and supports searching across processed documents. It also routes low-confidence extractions to a human review queue.
Yes. The description explicitly states that low-confidence extractions are sent to a human review queue for further confirmation.
The provided materials do not include installation steps, runtime requirements, or API key details. Please see the source repository for prerequisites.
Convert, extract, and process documents through an MCP interface for AI assistants.
Composable MCP tools for querying, indexing, classifying, and extracting document intelligence.
Extract images from PDF and Word files for reuse, review, and analysis.
Enable AI to extract text, analyze structure, and understand documents deeply.
Extract text, images, and tables from PDFs with multilingual analysis.
Search enterprise documents in natural language across PDF, PPT, and Word files.