Packages

Provides an MCP (Model Context Protocol) server that exposes FFmpeg-backed tools for common video and audio editing tasks such as format conversion, trimming, resizing/aspect changes, codec/bitrate/frame-rate adjustments, overlays (text/images), subtitle burning, concatenation/transitions, and audio operations like silence removal and format/property conversion. Includes a health_check tool.

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Provides an MCP server (Node/TypeScript) that wraps yt-dlp to let AI agents search for videos, extract metadata, download subtitles/transcripts, and download video/audio (including trimming), via MCP tools such as ytdlp_search_videos and ytdlp_download_video/audio.

Twitter/X API v2 for reading and posting tweets, searching public content, accessing user data, and streaming real-time tweet events.

MCP server that enables AI agents to interact with Android devices through ADB and Accessibility APIs, supporting gestures, typing, screen capture, and shell commands without requiring computer vision or OCR.

An MCP server that bridges BloodHound's Active Directory attack path analysis database to AI assistants, exposing 75+ tools for querying AD attack paths, privilege escalation routes, Kerberos vulnerabilities (Kerberoasting, AS-REP roasting), NTLM relay opportunities, and Active Directory Certificate Services (ADCS) misconfigurations via natural language. Instead of writing Cypher graph traversal queries manually, security professionals can ask an AI 'show me all paths from a Domain User to Domain Admin' and get results from their BloodHound Neo4j database. Designed for authorized penetration testing engagements where BloodHound data has already been collected from target AD environments.

crawl4ai-mcp-server is a self-hosted MCP server (stdio) that exposes Crawl4AI scraping/crawling capabilities to AI agents via four MCP tools: scrape, crawl, crawl_site, and crawl_sitemap. It supports Markdown extraction, BFS crawling with depth/page limits and optional adaptive stopping, and can optionally persist results to disk via output_dir/manifest files, while applying URL safety blocks for localhost/private/internal targets.

Provides an MCP server that automates Mozilla Firefox via WebDriver BiDi using Selenium/WebDriver. Exposes MCP tools for navigating pages, interacting with elements by UID, capturing screenshots, handling network/console events, and optionally using privileged contexts (requires extra system access).

Provides an MCP tool to query and summarize chat messages stored in a local SQLite database populated by a companion chatbot application. Exposes a single `query_chat_messages` tool for retrieval and AI-driven summarization.

memcp is a Python MCP server that provides persistent external memory for Claude Code. It stores insights in SQLite (including a MAGMA 4-graph with semantic/temporal/causal/entity edges) and larger context content on disk, exposing 24 MCP tools for remembering/recalling, context-as-variable management, searching, graph traversal, cognitive reinforcement/consolidation, retention lifecycle operations, and project/session organization. It also supports pre-compact auto-save hooks and can deploy RLM-style sub-agents for analysis/mapping/synthesis/entity extraction.

Provides a lightweight OAuth 2.0 authorization-code callback handler by spinning up a temporary localhost HTTP server to receive the redirect, returning the authorization code (and state/extra query params). Also includes an MCP (Model Context Protocol) SDK integration via a browserAuth provider with configurable token storage (in-memory or file-based) and support for dynamic client registration.

MCP server for Fibery — a flexible work management and knowledge base platform. Enables AI agents to read and manipulate Fibery databases, create/update entities, run queries, and interact with Fibery workspaces for project management, product development, and knowledge management workflows.

Provides MCP (Model Context Protocol) server tools that let AI clients run code and manage files inside E2B sandboxes. Includes separate JavaScript/TypeScript and Python implementations, offering sandbox lifecycle management, code/command execution, filesystem operations, and optional exposure of sandbox services via public URLs.

> AIが、あつらえる — AI-crafted video editing

# vMCP - Virtual Model Context Protocol

[](https://www.python.org/)

Bilibili video search MCP (Model Context Protocol) service - 哔哩哔哩视频搜索MCP服务

<!-- mcp-name: io.github.ariffazil/arifos-mcp -->