A
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qualityA
maintenanceA 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.
AGPL 3.0
72,476 servers. Updated
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"How to write a Java application, especially using Spring" matching MCP servers:
- Flicense-qualityBmaintenanceMCP server that converts PDF, video, web, and audio inputs into structured Markdown notes with support for checkpointing, batch processing, and Obsidian integration.
- Alicense-qualityDmaintenanceA 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.1MIT
- Alicense-qualityCmaintenanceAn 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.MIT
- Flicense-qualityCmaintenanceFetches category data from a Q&A service API and returns a markdown summary grouped by category.
- Flicense-qualityCmaintenanceEnables natural language management of Gmail through MCP tools for searching, analyzing, summarizing, drafting, and sending emails, with AI reasoning and user confirmation for actions.
- AlicenseAqualityDmaintenanceA 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.432MIT
DeepL MCP Serverofficial
AlicenseAqualityAmaintenanceA Model Context Protocol server that enables AI assistants to translate and rephrase text between numerous languages using the DeepL API.13467110MIT- AlicenseAqualityBmaintenanceAnalyzes YouTube videos using Google's Gemini API, allowing users to get summaries or ask questions about video content via direct URL input.5202MIT
- AlicenseAqualityBmaintenanceA privacy-first, zero-cost AI assistant that lets you chat with your documents locally via CLI or web app, supporting search, summarization, and Q&A using your own model.7MIT
- FlicenseAqualityBmaintenanceConverts subtitles or text into a single 1080×1620 infographic card (HTML+PNG) using LLM to generate content and Puppeteer for rendering.3
- AlicenseAqualityCmaintenanceThis TypeScript-based server implements a simple notes system using MCP concepts, enabling users to create, list, and summarize text notes through natural language prompts.31,655295MIT
- AlicenseAqualityDmaintenanceA TypeScript-based Model Context Protocol server that fetches, searches, and formats news articles from NewsAPI.org into reader-friendly Markdown digests using LLMs (Gemini and Claude).12696MIT
- AlicenseBqualityDmaintenanceA Node.js implementation of the Kagi Model Context Protocol server that enables Claude AI to search the web and summarize documents, videos, and audio using Kagi's APIs.213MIT
- FlicenseBqualityDmaintenanceA simple TypeScript-based MCP server that implements a notes system, allowing users to create, list, and generate summaries of text notes via Claude.13
- FlicenseBqualityDmaintenanceA TypeScript-based MCP server for handling a simple notes system with NextJS that supports creating and summarizing text notes using MCP concepts.44
- FlicenseBqualityDmaintenanceAllows you to search the web using DuckDuckGo and optionally fetch and summarize content from search results.24
- AlicenseBqualityDmaintenanceA simple note storage system that allows creating, storing, and summarizing notes with customizable detail levels.2MIT
- FlicenseBqualityDmaintenanceA simple note storage and management system that allows users to add, access, and summarize notes through a custom URI scheme. Supports creating summaries with configurable detail levels and provides real-time resource change notifications.4
- FlicenseBqualityFmaintenanceEnables intelligent web searching using SearXNG with content crawling via Creeper, then summarizes webpage content using LLM to avoid token limit issues. Supports smart filtering with domain blacklist/whitelist and optional LLM-based relevance filtering.1