"Servers that support Server-Sent Events (SSE)" matching MCP servers:

MCP server for Differino that lets AI agents compare PDF, DOCX, and TXT documents, with tools for visual and text diffs, summaries, exports, and account balance checks.

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

An MCP server that provides local, private, synchronous access to Ollama models for prompt answering, text classification, and model listing, without any file access or command execution.

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.

MCP server that fetches YouTube video transcripts and optionally summarizes them. Supports multiple transcript formats (text, JSON, SRT, WebVTT), multi-language retrieval, and flexible YouTube URL parsing.

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

Exposes support case reasoning tools — generate structured case briefs and check escalation readiness from any MCP-compatible AI client.

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.

An MCP server that converts PDF files to Markdown format using AI sampling capabilities, supporting both local files and URLs with incremental conversion features.

An MCP implementation that integrates the Brave Search API, providing comprehensive search capabilities including web, local business, image, video, news searches, and AI-powered summarization.

An MCP server that exports PDF documents to markdown format optimized for LLM processing.

Enables fetching, searching, and summarizing YouTube video transcripts with multi-language support.

A single MCP server that merges three context-engineering ideas into one toolset for AI agents

A Model Context Protocol server that enables AI assistants to translate and rephrase text between numerous languages using the DeepL API.

MCP server that compresses markdown files into caveman-style prose, cutting token usage by 65% while preserving code and structure.

Provides 14+ character-level text analysis tools that give LLMs the ability to accurately count letters, analyze individual characters, and work with text at the character level—overcoming tokenization limitations.

A Python-based server that provides access to Whissle API endpoints for speech-to-text, diarization, translation, and text summarization.

A Python MCP server for web research that enables fetching web pages, searching, batch-fetching, extracting links, and summarizing content via client-side sampling, with optional local file access.

A local content summarization service that allows AI agents to fetch web pages, WeChat articles, and Bilibili videos, transcribe if needed, and generate Markdown summaries via MCP.

Local MCP server that enables delegating low-risk tasks like summarization or code patches to a low-cost model, with the main agent reviewing results.

Provides MCP tools for querying and summarizing Northwest A&F University campus information, including trending QQ channel posts, official website notices/events/competitions, and cross-site custom searches with Markdown output and source links.

An MCP server that enables web searching, URL content extraction, and summarization without requiring API keys. It also provides advanced mathematical evaluation and multi-language Wikipedia summary retrieval tools.

A 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.

An MCP server for intelligent YouTube video analysis that provides token-optimized summaries, sentiment analysis, and entity extraction from transcripts. It enables AI assistants to perform video reporting, channel monitoring, and comprehensive YouTube searches through structured data tools.

Enables reading and extracting content from PDF documents including text (as Markdown), images, tables, and metadata from both local files and URLs, with OCR support for scanned documents.

A TypeScript-based MCP server that implements a simple notes system, allowing users to create, access, and generate summaries of text notes via URIs and tools.

MCP server that provides web content fetching, summarization, comparison, and extraction capabilities, handling up to 20 URLs per request.

A Model Context Protocol server that enables access to YouTube video content through transcripts, translations, summaries, and subtitle generation in various languages.

An MCP server that enables users to read, search, and analyze PDF documents. It provides tools for extracting text, viewing metadata, searching content with context, and generating word statistics.