"How to review merge requests in GitLab" matching MCP servers:

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

Summarizes Slack activity and GitLab merge requests with OpenAI to help generate daily standups, weekly reports, or quarterly check-ins.

MCP server that converts PDF, video, web, and audio inputs into structured Markdown notes with support for checkpointing, batch processing, and Obsidian integration.

Automatically generates comprehensive merge request summaries from git logs, analyzing commit history and categorizing changes into structured descriptions. Provides tools to analyze git repositories, compare branches, and create detailed summaries with change categorization, impact analysis, and review time estimates.

A 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.

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.

Enables MCP clients to search arXiv and OpenAlex literature and generate structured literature survey Markdown with normalized paper metadata.

A 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.

Enables GitHub-shaped tool calls to list issues, retrieve pull requests, and summarize them, while refusing merge-via-apply operations and remaining a local proof rather than making production changes.

Connects an AI assistant to the user's own WhatsApp groups so it can summarize activity, search stored summaries and messages, review join requests, and manage group settings when permitted.

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.

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).

Youtube, readable in AI chats.

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.

An MCP (Model Context Protocol) server specialized in deciphering PDF internal structures.

Enables LLMs to interact with Fathom.video API for managing meeting recordings, retrieving transcripts and AI-generated summaries, searching meeting content, and accessing analytics and team data.

Enables natural language interaction with local .docx files, allowing users to find, read, search, and summarize Word documents using friendly names and location hints.

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.