"ZDF" matching MCP servers:

Enables MCP clients to extract tables and text from digital PDF invoices, bank statements, and bills into CSV, JSON, or Excel, with automatic PII redaction by default.

Provides deterministic, schema-driven structured data extraction from PDF documents via regex/heuristic matching, enabling repeatable, inspectable, and cost-free field extraction without LLM API calls.

A Model Context Protocol server that extracts and processes content from PDF documents, providing text extraction, metadata retrieval, page-level processing, and PDF validation capabilities.

Enables interaction with Azure Data Factory instances, allowing users to list, read, create, update, and trigger pipelines, datasets, linked services, and runs through natural language.

An MCP server that exposes Azure Data Factory operations as tools any LLM can call — trigger pipelines, monitor runs, inspect datasets, and get factory health summaries through natural language.

Enables inspecting local PDFs and extracting tables into CSV, XLSX, or JSON with options for pages, merging, OCR, engine selection, headers, merged cells, regions, and columns.

Classifies PDFs (text-based vs scanned vs image vs mixed), extracts text, and converts to clean Markdown over Streamable HTTP MCP. Supports remote PDFs via URL or base64, with optional page restriction and OCR fallback detection.

Enables read-only monitoring and root-cause analysis of Azure Data Factory resources through MCP, allowing users to inspect factories, pipelines, and pipeline runs and diagnose failures via natural language.

Provides a read-only MCP interface for Azure Data Factory monitoring and root-cause analysis, with a health check for MCP clients.

A server providing PDF form manipulation tools via MCP's API, allowing users to find PDFs across directories, extract form field information, and visualize form fields in documents.

Enables Claude to diagnose and fix Azure Data Factory pipeline failures with automated rollback.