"A tool or method for searching within PDF files" 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.

Enables Claude Cowork on Windows to read, write, edit, list, find, and regex-search files inside a WSL distribution over stdio, accepting Windows and Linux path spellings. Access is confined to server-fixed roots, with secrets files refused, key-shaped strings redacted, and no delete or move operations.

Generates test files locally (images, PDFs, CSVs, corrupted files, etc.) from natural language prompts, with configurable sizes and safety limits.

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

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

A local vector database system that provides LLM coding agents with fast, efficient semantic search capabilities for software projects via the Message Control Protocol.

Semantic navigator for MCP tools that finds relevant tools by natural language intent, reducing token usage by 95%.

Enables AI agents to search and query the public DOJ Epstein Files release across 20 databases, resolve EFTA numbers to official DOJ PDFs, and cross-check viral claims against a fact-checked registry.

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.

Enables AI assistants to access and inspect local files within a specified sandbox root.

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.

A PDF MCP server for extracting text, rendered pages, tables, links, annotations, outlines, metadata, and text statistics from PDF files.

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.

Exposes semantic search over a folder of indexed PDF guides as a tool that Claude Code or any MCP client can call. Returns the closest matching passages with relevance scores, source file and page citations, so the client can answer questions about the guides while knowing when nothing relevant was found.

Memory-efficient MCP server for reading and splitting large PDF files page by page using PyMuPDF.

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.

An MCP server for high-quality bidirectional PDF ↔ Markdown conversion with full Unicode/CJK character support, enabling users to convert files via natural language commands.

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.

Provides A-share (Chinese stock market) quantitative analysis through tools for stock screening, northbound capital flow tracking, dragon-tiger list analysis, margin trading, sector analysis, technical indicators, IPO info, and limit-up/down statistics using akshare data.

Enables AI agents to perform local-first PDF processing entirely on-device, including OCR write-back to make scans searchable, unlocking and re-encrypting PDFs, splitting/merging/rotating pages, and compressing files, with no cloud calls or file uploads.

mcp using PyPDF2 to: • merge-pdfs • extract-pages • search-pdfs • merge-pdfs-ordered (merge in user spec. order) • find-related-pdfs (regex extracted text for related PDF files)

Enables AI models to perform file operations, user management, automations, and more within Files.com's secure file transfer platform via the Model Context Protocol.