"Translation service or tool" matching MCP servers:

An offline MCP server for translating movie subtitles, providing persistent translation sessions, a glossary, and modular format adapters so LLM agents can translate while timing is never altered.

MCP server for translating PDFs using pdf2zh-next, preserving document context by extracting all text segments for LLM translation at once.

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.

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.

Provides transactional intelligence for AI agents, enabling safe tool execution with pre-flight invariant checks, sub-second filesystem snapshots/rollback, causal tracing, belief contradiction detection, and 15 native MCP tools for Claude Code.

Enables atomic batch find-and-replace edits across single or multiple files, reducing tool calls and token usage for efficient code refactoring.

Enables extraction of recipes from PDFs or JPG files and conversion into structured HTML, with interactive region selection and OCR via a web GUI.

MCP server for managing i18n JSON translation files. Provides Claude with structured read/write access to translation files for adding keys, checking coverage, and finding duplicates.

Enables an LLM agent to search files, list directories, read and write UTF-8 text files, move or delete paths, list terminal processes, and launch a terminal in a chosen folder.

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.

Encoding-aware, indentation-smart file tools for AI coding agents. 20+ tools including read/edit with automatic encoding detection, smart indentation conversion, SSH, SFTP, process management, and system utilities.

Enables local OCR transcription of images using tesseract.js, with optional low-token AI-generated descriptions, folder batch processing, and compatibility with MCP clients like ChatGPT, Claude, opencode, and Cursor.

Enables automatic discovery and fast searching of translation files in projects, supporting partial/exact key-value matching with file watching and multiple translation file formats.

A Model Context Protocol server for secure, sandboxed file operations and project scaffolding with built-in search and regex capabilities. It is optimized for Windows environments and features configurable access controls to restrict operations to specific directories.

Enables execution of shell commands through a terminal tool and provides access to a custom readme file from OneDrive Desktop or local Desktop directory.

An MCP server that helps AI agents reduce token usage by converting data to TOON format and stripping comments and unnecessary whitespace from code files.

This server is to precess files for LNR.

Adds workspace-scoped copy, move, and delete tools to DevSpace so filesystem changes are validated against workspace boundaries and protected paths instead of relying on shell cp, mv, or rm commands.

Local MCP server enabling Codex and ChatGPT to read/write files, execute commands, manage processes, use Git, and inspect images on the user's machine with full privileges.

A local AI agent system that gives any LLM real access to the filesystem, terminal, and codebase via MCP, usable as a standalone terminal agent or Continue.dev integration in VS Code.