"A tool or method for searching PDF documents" matching MCP servers:

A production-ready MCP server for Method CRM API integration. It enables LLMs to interact with Method CRM data through tools for tables, files, users, events, and API key management.

MCP server that provides OpenRouter model pricing data, enabling price lookups, trending/cheapest lists, and model searches without an API key.

Full-stack PDF intelligence MCP server for extracting, manipulating, annotating, converting, validating, and RAG-searching PDFs through a unified tool surface and React workbench.

Enables interactive chat with AI models, including document retrieval and command-based prompts via the Model Control Protocol.

Let your AI assistant create professional Office documents — PowerPoint, Word, Excel, emails & XML — with a single prompt.

An MCP server that exposes Marker for high-quality PDF OCR and conversion, providing a tool to convert PDFs to markdown, JSON, or HTML with optional LLM-enhanced mode.

This server converts PDFs to markdown with intelligent academic paper detection and dual processing engines (marker-pdf for academic content, PyMuPDF for general documents), supporting URL and local file handling, page extraction, batch processing, and PDF link crawling for Claude Code analysis.

Enables AI assistants to natively read, edit, and redact PDF documents in place through MCP tools, eliminating manual script execution and layout issues.

MCP router that fronts your other MCP servers behind a few small generic tools, so their tool definitions stay out of the context window and are discovered on demand.

A local-first MCP server that ingests PDFs, extracts structure, and provides semantic search and sequential navigation tools for AI clients to query and learn from documents.

Enables PDF processing and analysis including text extraction, metadata retrieval, search, page manipulation, splitting/merging, conversion to images, and form handling.

Enables generation of PDF documents from JSON specs or Markdown, supporting themes, tables, images, and other rich blocks.

An MCP server for reading, rendering, and searching PDF files, specifically optimized for LLMs to extract text, tables, and technical diagrams. It enables metadata retrieval, multi-format text extraction, and page-to-image rendering using PyMuPDF.

Converts Markdown files to Word (.docx) and PDF documents. Supports .dotx templates for branded styling and batch conversion.

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 comprehensive tool server for reading, merging, and extracting content from PDF files via local paths or direct URLs. It enables metadata retrieval, regex searching, and page-specific text extraction with built-in caching and workspace-restricted security.

A Model Context Protocol server that enables AI agents to read, search, and extract content from PDF files.

PDF Reader MCP Server for VS Code

Enables MCP clients like Claude to query Chinese A-share market data, including K-line charts with forward/backward adjustment, limit-up and limit-down pools, per-stock fund flows, index quotes, and stock news, with automatic symbol normalization and retry handling for throttled data sources.

A server designed for processing PDF documents, enabling text extraction, table data retrieval, and metadata collection from local files. It allows users to scan directories for PDFs and read specific pages, specifically optimized for thesis literature analysis.