"Steps to Internationalize and Localize My Application with Translations" matching MCP servers:

A local-first, open-source MCP server that analyzes jobs, matches your CV, tailors documents, and tracks applications — all on your machine with no data uploaded.

MCP server that converts PDF, video, web, and audio inputs into structured Markdown notes with support for checkpointing, batch processing, and Obsidian integration.

A Model Context Protocol (MCP) server that automates generating LinkedIn post drafts from YouTube videos. This server provides high-quality, editable content drafts based on YouTube video transcripts.

A note management MCP server that enables users to store, retrieve, and summarize personal notes via a custom URI scheme. It provides tools for adding content and prompts for generating brief or detailed summaries of stored information.

MCP server for aggregating and analyzing hot news from multiple platforms, with AI-powered summaries, smart filtering, and multi-channel notifications.

Enables exploring Steam store reviews and community discussion threads with server-side filtering, temporal analysis, and metadata context for understanding player sentiment and feedback beyond store page noise.

A TypeScript-based MCP server that enables users to manage text notes and generate summaries, showcasing key MCP concepts like resource representation and LLM integration.

Integrates local language models (like Qwen3-8B) with MCP clients, providing tools for chat, code analysis, text generation, translation, and content summarization using your own hardware.

A Model Context Protocol server that implements a simple notes system, allowing users to create, list, and summarize text notes.

This MCP server enables users to analyze YouTube videos by extracting transcripts and generating specialized content like summaries, chapter timestamps, and social media posts.

Enables Claude to read and analyze PDF documents with automatic OCR processing for scanned files. Features intelligent text extraction, caching for performance, and secure file access with search capabilities.

tooltrim reduces the tokens agents spend re-reading bloated tool results. Run it as an MCP server exposing compress and expand_tool_output, or as a gateway in front of any upstream MCP server: it re-exposes the upstream tools unchanged and shrinks each result (HTML/JSON/logs/tables) before it reaches the model, keeping the relevant content only.

Lets any AI agent score and simplify its own text before it reaches a human, using Flesch readability metrics and plain-language rewrites entirely on the local machine.

MCP server that searches the web, reads pages, and returns concise summaries with cited sources via the research_web and read_url tools.

A FastMCP server that enables AI assistants to extract structured information from unstructured text using Google's langextract library through a secure, optimized Model Context Protocol interface.

Enables LLMs to interact with Fathom.video API for managing meeting recordings, retrieving transcripts and AI-generated summaries, searching meeting content, and accessing analytics and team data.

Integrates Vale prose linting into AI coding assistants, enabling users to check text files for style and grammar issues using Vale's powerful linting engine. Provides automated style feedback with smart configuration discovery and rich formatted results.

Enables natural language interaction with local .docx files, allowing users to find, read, search, and summarize Word documents using friendly names and location hints.

Provides MCP-compatible AI clients with offline text analysis and rewriting tools, including statistics, extractive summaries, keywords, readability scores, case conversion, entity extraction, and diffing, all running locally without API keys or network calls.

Enables AI agents and MCP clients to browse Roomtone meeting notes, add YouTube or pasted-text sources, generate summaries, ask questions answered from transcripts, and retrieve raw transcript text. Recording itself stays in the Roomtone app, so the server only reads and adds to existing meetings.

Enables production-grade web research through MCP, combining local SearXNG search with hosted fallback providers, fetch and crawl tools, summarization, and budget guardrails.

Enables context compression for Claude Code with Thai language support, reducing token usage by 50-88% while preserving full recoverability of original content.

Unofficial MCP server for working with Kagi without API access (you'll need to be a customer, tho). Searches and summarizes. Uses Kagi session token for easy authentication.

Analyzes unstructured documents in a local folder, extracting structure and key terms, and supports generating summaries via a host LLM with validated, approval-based report saving.

MCP Long Context Reader is a Python-based toolkit designed to overcome the context window limitations and high costs associated with Large Language Models (LLMs) processing extensive documents. It provides a FastMCP server with multiple, powerful strategies for an LLM agent to 'read' and query long documents without needing to load the entire text into its context window.

Enables any LLM to process arbitrarily long contexts through recursive decomposition, without requiring external LLM APIs.

Enables users to extract and review Claude's plan reasoning in Claude Code by reading plan files and providing a structured template for decisions, tradeoffs, and assumptions.

An MCP server providing secure calculation, knowledge base search, and text statistics tools, along with resources and prompts for enterprise agent integration.

Provides accurate meeting transcription with speaker diarization and multilingual support, allowing users to submit audio URLs, poll transcription status, get transcripts, and summarize via MCP tools in their IDE.

Generates natural, fluent Chinese content that reads like human writing using the Qwen3-Next-80B-A3B model. Supports web search for latest information and direct file saving with customizable writing rules.