"Resources and Information on Video Game Development" matching MCP servers:

Extracts transcripts or spoken captions from multi-platform video links (Bilibili, YouTube, Douyin) and returns concise Markdown summaries or full transcripts, saving tokens by keeping full text out of the conversation.

Enables automated video learning workflows by ingesting video URLs, managing remote GPU ASR transcription, pulling transcripts, generating digest summaries, and searching local notes via MCP tools.

Extracts captions, metadata, and descriptions from YouTube videos to enable AI assistants to summarize their content.

Enables AI assistants to analyze and summarize YouTube videos by extracting captions, subtitles, and comprehensive metadata including title, description, and duration in multiple languages.

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.

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 simple note storage system that lets users create and summarize notes with varying detail levels using Claude.

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.

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.

MCP server for koreafilings.com — AI-summarized Korean DART (전자공시) corporate disclosures, paid per call in USDC via the x402 protocol on Base. Tools: get_pricing (free), get_disclosure_summary (0.005 USDC).

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.

Allows AI agents to fetch, search, and summarize YouTube video transcripts without an API key, including chapter summaries.

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.

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.

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.

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.

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

Enables transcription, summarization, and action item extraction from audio files on your Mac using MacWhisper and Claude Desktop, all locally without any cloud APIs.

Enables agents to check and retrieve concept-structured YouTube video summaries from the oratilo library via lookup and full-text search tools, avoiding redundant summarization work.

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.