"Information about playwrights or the Playwright framework" matching MCP servers:

A proxy MCP server that summarizes Playwright accessibility snapshots using Claude Haiku, reducing context usage for efficient browser automation.

Enables AI agents and assistants to retrieve Indian news briefs synthesized from many outlets, including corroboration counts, framing comparisons, daily digests, topic alerts, and Breaking News, through public and account-authenticated tools over Streamable HTTP and OAuth.

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.

Measures AI-detection risk in text and provides a line-by-line rewrite plan to lower the score.

Self-hosted digests of your Telegram channels over MCP: AI summaries, the last digest and raw per-channel messages. Works with OpenAI, Anthropic or local Ollama.

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).

Two self-hosted MCP servers: manage a local model machine (Ollama pull/switch, LoRA training) and bridge to local Ollama/vLLM for pure language processing tasks (writing, summarizing, classifying, extraction) without giving the calling agent tools or file access.

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.

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.

Model Context Protocol server exposing the bankstatementparser library as first-class agent tools for reading bank statements.

Exposes the Aporix document optimization API as an MCP tool for AI agents, enabling document compression and token/cost savings analysis.

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.

MCP server for HumanPen that lets AI agents work on real documents (.docx, .pptx, .pdf) — humanizing content to lower AI-detection scores, converting citations, condensing, and translating while preserving formatting, tables, images, and citations.

Turns plain text or Markdown, web pages, and local PDFs into editable Markdown outlines that can be rendered as standalone, offline-capable interactive HTML mind maps. Works with any MCP client with no API key required, since the connected model writes the final outline from a draft and cleaned source text.

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.

An open-source MCP server for querying the Tenarius RO wiki and Ragnarok Online Pre-Renewal references. It provides structured search and summaries with source metadata indicating server and era applicability.

Enables an assistant to transcribe video or podcast recordings, then read, search, summarize, and manage the resulting transcripts through MCP tools.

Fetches, parses, and summarizes ETSI telecommunications and media standards documents, enabling Claude to autonomously look up and ingest standards mid-conversation for answering questions, generating conformant code, or writing XML.

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.

Enables AI assistants to transcribe links (YouTube, Google Drive, Dropbox), list and search your recordings for spoken words and moments, and read transcripts in json/txt/srt/vtt, summaries and metadata. It also lets them request new summaries and delete recordings, all through your own account with API-key or OAuth sign-in.

Enables coding agents to offload reading and summarizing multiple large files to a cheaper worker LLM, keeping full file contents out of the main agent's context.

Enables AI agents to search, watch, summarize, clip, and extract transcripts from YouTube videos, all without needing an API key or leaving the chat.

Enables agents to analyze large logs by clustering messages with Drain3 and returning a representative set of snippets from provided text, files, URLs, or compressed archives.

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

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.

Enables fetching and analyzing YouTube video comments and replies through the YouTube Data API. Supports sorting by relevance or time and returns structured JSON data for comment analysis, summarization, and translation tasks.

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

Enables analysis of YouTube videos using the Gemini API to generate summaries and answer specific questions via direct URLs. It supports standard videos and shorts, allowing users to interact with video content without requiring manual downloads.

A Python MCP server for fetching and summarizing news articles from the Boring News API by date, category, tags, people, and similarity.

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.

Routes narrow text-processing tools (classification, extraction, summarization, etc.) to budget models to reduce token consumption on the main model.

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.

Provides AI tools for chat, code review, idea evaluation, explanation, summarization, and debugging by automating DeepSeek AI through Playwright.

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 the Fathom AI meeting intelligence API