A
licenseNot graded
qualityD
maintenanceLocal MCP server that indexes folders of documents into a hybrid vector + keyword search index for Claude Desktop, with support for PDFs, Office files, and images via OCR.
MIT
mcp-docparser
by Jasonzld
Related Servers
Alternatives to mcp-docparser
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityAmaintenanceMCP server that exposes GroupDocs.Parser as AI-callable tools for extracting text, images, metadata, tables, barcodes, and document info from 50+ document and image formats.MIT
- AlicenseNot gradedqualityDmaintenanceUniversal MCP server for extracting text from various document formats including PDF, Excel, Word, CSV, and more, with support for streaming, limits, and markdown conversion.3MIT
- FlicenseNot gradedqualityDmaintenanceMCP server enabling Claude Desktop to answer questions from local Word and PDF documents by searching a vector index built from their contents.-
- AlicenseNot gradedqualityCmaintenanceMCP server that gives your Claude, Cline, or Cursor session the ability to extract text, tables, and metadata from any PDF URL — including scanned PDFs via OCR.MIT
- FlicenseNot gradedqualityDmaintenanceAn MCP server that enables Claude to perform OCR on local files using Mistral AI's document processing capabilities. It converts documents and images into markdown format for seamless analysis and interaction.-
TDQS
B3.1/5.0
Scored across 7 tools
Disambiguation2/5
Multiple tools have overlapping purposes: parse_document, extract_text, and ocr_image all extract text from images/documents, with descriptions that are nearly indistinguishable. analyze_image also overlaps with get_document_info for image metadata, making it hard for an agent to choose the right tool.
Naming Consistency4/5
All tool names use snake_case and most follow a verb_noun pattern (e.g., analyze_image, chunk_document, get_document_info). batch_ocr and ocr_image deviate slightly by starting with a noun or acronym, but the overall convention is clear and readable.
Tool Count5/5
Seven tools is well-scoped for a document parsing server, providing distinct capabilities for parsing, OCR, text extraction, metadata, image analysis, and chunking without being overwhelming or thin.
Completeness4/5
The surface covers core document parsing tasks: parsing, text extraction, OCR (including batch and language support), metadata retrieval, image analysis, and chunking. Minor gaps exist, such as tools for output saving or format-specific handling, but agents can work around them.
Maintenance
ActivityInactive
ResponsivenessNo issues