"Document analysis tools for legal documents and evidence" matching MCP servers:

An MCP server that converts and processes document formats such as DOCX and PDF into Markdown, enabling AI assistants to work with document contents.

Enables AI assistants to convert and process various document formats through an MCP server interface.

A production-ready Model Context Protocol server that bridges local document management with cloud synchronization (Notion) for AI agent integration, enabling seamless access and sync of local and cloud documents.

Enables AI agents to perform local video, audio, and file operations inside an isolated workspace, including cutting/concat videos, extracting audio, transcribing, and managing files, with typed responses and background job support.

This MCP server enables reading and analyzing various file formats, including PDF, DOCX, XLSX, and CSV, by extracting metadata, searching for keywords, and reading structured content. It also provides capabilities to create new documents and convert files between supported formats.

Enables document conversion and processing through an MCP server interface for AI assistants.

A local AI document assistant MCP server that enables listing, reading, and editing documents via tools, resources, and prompts, allowing LLMs to manage document workflows through natural language.

A multi-format MCP server that enables reading and generating Office, PDF, text, EPUB, and presentation documents. It provides unified tools for document processing and creation through AI assistants.

An MCP server providing an append-only, hash-chained evidence ledger for agent actions, where every record is a tamper-evident receipt cryptographically bound to all prior records and persisted as human-readable JSONL local state. It exposes tools to append records, verify chain integrity (pinpointing tampering), query records by actor/action/target/time, and fetch ledger stats—with no update or delete capabilities by design.

The local PDF workflow for Claude Desktop and MCP hosts: fill, sign, merge, split, extract, and analyze PDFs without sending files to a web app.

A local evidence recorder that captures screenshots, recordings, notes, and summaries during long-running agent tasks, enabling reviewable task records with timelines and artifacts.

Enables agents to capture task-scoped residue evidence during test and build workflows, exposing files, directories, processes, and ports for user-authorized cleanup and post-cleanup verification without deleting or modifying anything itself.

Enables reading and searching documents in allowlisted folders via LiteLLM and MCP tools, using COM for Office files to support IRM-protected content.

Enables conversion between PDF/Office documents and structured JSON, supporting extraction and generation of document content.

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 document conversion between PDF, DOCX, and Markdown formats to facilitate reading and editing complex files in AI tools like Claude Desktop or Cursor. It utilizes marker-pdf and pandoc to provide structured text versions of documents, helping to manage context and support unsupported file types.

Converts between Markdown and Word documents using pandoc, with support for conversion options, pandoc installation check, and listing supported formats.

Enables parsing and extraction of content from various document formats (PDF, Word, Excel, PowerPoint) into Markdown format using the Niutrans document API.

MCP server for managing product documentation as markdown files. Supports creating, reading, updating, deleting, and searching docs with optional semantic search.

Enables clients to inspect local PDFs by searching text, rendering pages, and cropping selected regions at high resolution directly from the source document. It runs locally over stdio without requiring models, embeddings, GPUs, or API keys, and does not modify source PDFs or send network requests.

Enables MCP clients to search, read, and record reviewed conclusions from policy-gated allowlisted files, with sanitized chunks and create-only drafts or append-only lessons, without granting general filesystem or execution access. It supports lexical ranking and optional loopback embeddings while rejecting likely credentials and raw challenge flags.

Converts documents between Markdown, PDF, DOCX, and HTML locally with AI-friendly Markdown output and secure file access.

Enables an agent to inspect an audio folder and report what is inside each file — duration, sample rate, channels, codec and bitrate — and to group byte-identical files, identical decoded audio stored in different containers, and near-duplicate candidates, with suggested keeps and explicit differences, all read-only.

Enables AI assistants to analyze, rename, categorize, and organize local documents using OCR, metadata extraction, and batch processing, with preview mode and undo support.

Search a folder of documents and check answers against them. Offline: no API key or database.

Enables MCP clients to extract text from PDF, image, Word, PowerPoint, and Excel files using MinerU, either on the local machine or a self-hosted private-network API. Parsed results are saved locally as Markdown, structured JSON, and extracted images, which can then be read back in segments.

MCP server for AI-assisted PDF reading with pagination, search, and page navigation.

Enables reading and processing various document formats including Word, PDF, RTF, and text files. Supports extracting media elements like images and links, with features for PDF page range selection and automatic text encoding detection.

Enables AI assistants to read, modify, and create Word (.docx) and Excel (.xlsx) files through natural language commands, including batch queries and temporary table management.

Enables creating, reading, editing, and verifying PDF, Word, Excel, and PowerPoint documents through MCP tools that return structured results. It preserves source files by default for edits and supports local stdio operation without network requests.