Nucleus Mcp

An MCP service designed for deploying HTML content to EdgeOne Pages and obtaining an accessible public URL.

A Model Context Protocol (MCP) server for image generation and manipulation using fal.ai's Stable Diffusion model.

Location services, directions, and place details

An MCP server implementation that provides a tool for dynamic and reflective problem-solving through a structured thinking process.

高德地图官方 MCP Server

Playwright MCP server

Web content fetching and conversion for efficient LLM usage

Browser automation and web scraping

An MCP server implementation for retrieving information from the AWS Knowledge Base using the Bedrock Agent Runtime.

MCP server to provide Figma layout information to AI coding agents like Cursor

Ready for a new way to bill pay? Pay any bill in a snap, right from a chat. Describe or snap a photo of your bill (electric, water, gas, internet, phone, medical, credit card, rent, parking tickets, traffic violations and more) and Papaya reads it, then hands you a secure link to pay by card. Fast, secure, and no juggling twelve logins, with full or partial payments and status updates. Powered by Papaya (papayapay.com).

A Model Context Protocol server that provides time and timezone conversion capabilities. This server enables LLMs to get current time information and perform timezone conversions using IANA timezone names, with automatic system timezone detection.

ContextBridge (CB) is a local-first retrieval layer that sits between your codebase and your AI coding agent. Instead of pasting raw source files into context or letting the AI guess which files matter, CB indexes your codebase's real structure (via Graphify) and returns a compact, ranked result — owner file, related files, key symbols, and dependency chains — grounded in your actual code. A typical response is ~4–8 KB instead of the 100+ KB of raw source an AI would otherwise need to read to answer the same question — roughly a 96% cut in input tokens sent to your cloud AI, with zero hallucinated file paths or method names.

Read-only database access with schema inspection

Official remote MCP server for Framesail AI. Create long-form (faceless YouTube) videos end to end from any MCP client: script, locked character references, storyboard, voiceover, and final video editing — with characters and style held consistent across every shot. Making long-form AI video today means 8+ tabs stitched by hand — an LLM for the script, a voice model, an image model, a video model — with characters drifting between tools and style resetting at every export. Framesail replaces the patchwork: the whole pipeline runs in one place and manages your video's context end to end. Six stages: Style (paste images, videos, or YouTube links and Framesail reverse-engineers the look, voice, and direction), Script (write it yourself or generate it in your narrative style), Reference images (auto-generated for every character, place, and prop), Voiceover (one narrator or many characters, with word-level timing), Storyboard (planned scene by scene), and Editor (captions, music, SFX, then export). No black box: you control every prompt, asset, model, and setting.