Enables local analysis of unstructured documents (PDF, DOCX, PPTX, SVG, PNG) by extracting text and structure with citation anchors, and verifies summaries against source material before a human approves saving a report.
Enables read-only scanning and text extraction from PDF, DOCX, PPTX, SVG, and PNG files in a local folder, providing the raw text to AI models for summarization or analysis without an external LLM API.
An HTTP MCP server that indexes large documents into exact-line-numbered sections, enabling AI models to locate, read, summarize, and edit parts of a document without ingesting the whole file.
Provides AI agents with document conversion to Markdown, intelligently routing small and large files, and enabling targeted extraction via sections, search, and token budgets.
This server provides an API to query Large Language Models using context from local files, supporting various models and file types for context-aware responses.
Enables comprehensive local file system operations including searching and reading content from various formats like PDF, Office documents, CSV, and text files. It features automatic character encoding detection and secure path validation for directory access.
Enables AI assistants to professionally edit Persian text by reading a draft, diagnosing its problems, and assembling a tailored checklist from a 1,577-note editorial knowledge base spanning orthography, punctuation, grammar, word choice, tone, and structure. It then runs staged cleanup, AI editing, independent review (up to four rounds), and final verification, returning a clean text plus a change report, and also exposes rule search, rule packs, and diff auditing for use in Claude Desktop, Cursor, n8n, or custom code.
Enables local analysis of scientific papers including PDF parsing, mathematical formula extraction with AST generation, PyTorch code generation from methodology, and automated Markdown report generation with visualizations.
Local MCP server that extracts text and structure from PDF, DOCX, PPTX, SVG, and PNG files, along with directory and metadata listing, for read-only document analysis by LLM hosts.
Enables Claude AI to perform comprehensive file operations including reading, writing, notes management, PDF processing, and image handling with thread-safe operations. Provides a complete file management system with enhanced features like document processing and automatic directory creation.
Parse any file or URL into structured text. Extract text from PDF, DOCX, YouTube, web pages, images, and 25+ formats via one API. Tools: parse_url, parse_file, get_youtube_transcript.
Local-first MCP server providing deterministic Flutter/Dart static analysis, knowledge search, and project review with structured insights and confidence-based findings over an indexed SQLite store of official repositories.
A tool that helps users conduct comprehensive research on complex topics by exploring questions in depth, finding relevant sources, and generating structured, well-cited research reports.
Enables local, read-only extraction of text and structure from PDF, DOCX, PPTX, SVG, and PNG files, including OCR for images, directory tree and metadata reporting, with strict path isolation and audit logging.
Enables automated README file management for development projects through MCP tools for content creation and summarization, resources for direct file access, and prompts for AI-powered documentation analysis.
Enables AI assistants to fetch sourced, citable face measurement percentiles, face type definitions and threshold rules, methodology and citation details, and to classify a face shape from four distances using the site's seven rules in order. Read-only and takes no photo.
Enables AI assistants to search and retrieve documentation, component specs, theme guides, and CLI commands for the Meta Astryx Design System, providing structured tools and guidelines for coding agents.
MCP server that enables AI assistants to drive systematic literature review workflows, including screening, downloading, converting, and reviewing papers through natural language conversation.
Enables searching and reading AVEVA Customer Support Portal knowledge base articles, including tech notes, known issues, and error-message diagnostics, to ground AI answers in support content not found in public documentation.
Provides AI assistants with current Ionic Framework v9 and v8 documentation, including component API references, usage examples for Angular, React, Vue, and vanilla JavaScript, and Ionic blog posts. Enables searching docs, reading pages, listing components, retrieving usage examples, and listing blog posts.
Provides fast, token-efficient search over coding agent documentation (e.g., Claude Code, Cursor) using local SQLite FTS5 indexing, with tools for searching snippets, reading pages, and grepping markdown.
Enables searching and reading AWS knowledge from sources the official AWS Knowledge MCP Server does not index, including re:Post community Q&A, kiro.dev documentation, and AWS Builder Center posts.
A Model Context Protocol server that enables AI assistants like Claude to interact with Outline document services, supporting document searching, reading, creation, editing, and comment management.
A Model Context Protocol server for querying and reading articles from a how-to documentation portal, with search and retrieval tools scoped to the token's user permissions.
Provides read-only tools for planning, writing, and auditing lesion network mapping and connectome-based localization papers, including design classification, methods checklists, phrasebooks, limitations, and manuscript auditing.
