Best MCP servers for extraction

MCP server comparison

Here's how the top MCP servers and document extraction tools compare for extraction:

1. Lido MCP — Best for structured extraction

Lido's MCP server connects directly to Claude, Cursor, and Windsurf with a single npm command. Unlike conversion tools that output markdown or raw text, Lido returns structured rows and columns — the fields, line items, and tables extracted from your documents and organized into data you can use immediately.

The extraction engine reads document layouts without templates. Point it at an invoice and it finds the vendor, amounts, and line items. Point it at a bank statement and it finds the transactions. No training, no zones, no rules to configure.

Strengths: Template-free structured extraction, native MCP support, OCR built in, SOC 2 + HIPAA certified, 50 free pages.

Limitations: Requires Lido account for production use, cloud-based processing (no on-prem option).

2. MarkItDown — Best for document-to-markdown conversion

Microsoft's open-source tool converts documents into markdown. It handles PDFs, Word docs, PowerPoint, and Excel files. The output is readable text rather than structured data, which means you still need to parse it to extract specific fields.

There's no native MCP server, but community wrappers exist. Good for general document reading; less effective for pulling structured data from documents.

Strengths: Open source, supports many file formats, good markdown output.

Limitations: No structured data output, limited OCR, requires wrapper for MCP, tables often lose structure in conversion.

3. Docling — Best for open-source document conversion

IBM's Docling is an open-source document conversion library that supports PDF, DOCX, PPTX, and other formats. It extracts text, tables, and images with a focus on preserving document structure.

Docling runs locally, which is useful for sensitive documents. The tradeoff is that you need to set up Python dependencies and a wrapper to use it via MCP.

Strengths: Open source, runs locally, good table detection, multiple output formats.

Limitations: Requires Python setup, no native MCP server, heavier resource requirements, output needs additional parsing for structured extraction.

4. LandingAI — Best for visual document understanding

LandingAI offers an MCP server focused on document understanding with vision models. It's particularly good at understanding complex page layouts and extracting content from visually rich documents.

Strengths: Native MCP support, good at complex layouts, agentic extraction capabilities.

Limitations: Outputs markdown (not structured rows/columns), limited free tier, cloud-only.

5. Koncile — Best for accounting-specific extraction

Koncile focuses specifically on accounting documents — invoices, receipts, and financial statements. Their MCP server is purpose-built for accounting workflows and outputs data in formats that integrate with bookkeeping tools.

Strengths: Accounting-focused, good at financial documents, purpose-built output format.

Limitations: Narrow document scope, limited to accounting use cases, less flexibility for general extraction.

How to choose an MCP server for extraction

The right tool depends on what you need the extracted data for:

Use Lido MCP if you need structured rows and columns from documents — fields extracted and organized into data you can pipe into code, databases, or spreadsheets. Lido handles any document layout without templates.

Use MarkItDown or Docling if you just need to read document contents as text. These tools convert documents to markdown, which your AI can then reason about. Good enough when you don't need structured field extraction.

Use Koncile if you're working exclusively with accounting documents and need output formatted for bookkeeping workflows.

Use Claude's built-in PDF reading for one-off questions about a document's content. No setup required, but the output is unstructured text rather than extracted fields.