"Information about 飞书 (Feishu)" matching MCP servers:

Fetches category data from a Q&A service API and returns a markdown summary grouped by category.

Provides clean, bounded web content to AI by filtering HTML noise and optionally summarizing, preventing context window overflow.

A small MCP server that gives agents rich context about a YouTube video — its transcript, jump-to-the-moment deep links, metadata, and most-replayed moments — so they can answer questions, summarize, pull quotes, or surface highlights.

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.

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.

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.

Unofficial MCP server wrapping crawl4ai that enables extraction and analysis of content from web pages, PDFs, Office documents, YouTube videos, and more, with AI-powered summarization and Google search integration to reduce token usage while preserving key information.

Analyzes YouTube videos using Google's Gemini API, allowing users to get summaries or ask questions about video content via direct URL input.

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.

distill-mcp-v2 is a high-performance, network-dependency-free Python FastMCP server designed to aggressively optimize Large Language Model (LLM) context windows. It provides specialized tools for compressing and analyzing massive AI-agent payloads without losing critical semantic information.

MCP server for Glanceway, the macOS menu bar information app, enabling AI assistants to read sources and items.

A Model Context Protocol server that provides tools for analyzing text documents, including counting words and characters. This server helps LLMs perform text analysis tasks by exposing simple document statistics functionality.

Enables LLMs to retrieve and analyze Steam game reviews, providing access to review statistics, game information, and helping summarize pros and cons of games.

Wraps the gpt-researcher tool as an MCP server, enabling automated web research, information summarization, and structured report generation via natural language queries.

A Model Context Protocol server that analyzes YouTube videos, enabling users to extract transcripts, generate summaries, and query video content using Gemini AI.

An 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.

A Model Context Protocol server that enables Claude to fetch, process, and extract information from PDF documents, including LaTeX mathematical equations.

Exposes TaskFleet's pay-per-call AI task APIs as MCP tools, including web search, scraping, extraction, translation, code review, summarization, and wallet intelligence. Payments are handled via x402 (USDC on Base) with no accounts or API keys.

MCP server for summarizing content from Baidu Netdisk, local files, Bilibili, X, and web articles, producing Obsidian notes with bidirectional links and Feishu digests.

Enables AI language models to interact with YouTube content through a standardized interface, providing tools for retrieving video information, transcripts, channel analytics, and trend analysis.