A powerful Model Context Protocol (MCP) server that provides an all-in-one solution for public web access.

Guarded context compaction for DeepSeek Harness (dsh): the LLM proposes, deterministic guards dispose — eager per-atom shrink (extract/summary/false under verbatim guards) + lazy reference-graph eviction (0-LLM) + byte-exact recall from an append-only log

🚀 自托管的抖音、TikTok、B 站数据采集与无水印视频下载 API，支持 AI agent 通过 MCP 调用与离线语音转文字，Docker 一键部署。| Self-hosted TikTok, Douyin & Bilibili scraper and no-watermark video downloader — async REST API, MCP server for AI agents, CLI and web console, plus offline speech-to-text for downloaded videos. Self-healing identity pool, PostgreSQL archive, one docker compose up.

MCP server that gives AI agents the web: fetch, search, crawl and screenshot from one local Rust binary. Zero API keys, zero accounts, Chrome-true TLS.

Stealth browser automation for AI agents over MCP and the Chrome DevTools Protocol: navigation, network hooks, DOM extraction, and pixel-accurate UI cloning.

WebCite MCP Server - verify AI claims against authoritative sources, bind quotes back to their source passage, and extract document figures deterministically. Works with any MCP-compatible agent or tool.

The missing tool to sift your Claude Code sessions: regex search across all record types, recover files, extract images, inspect subagent topologies, match between plan files and sessions.

Model Context Protocol (MCP) Server for Graphlit Platform

Enables AI assistants to access a user's Pusan National University Moodle-based LMS account, browsing courses, materials, notices, assignments, grades, calendars, and Q&A, downloading course files, and performing write actions like submitting assignments after a confirmation preview. It combines the official Moodle Web Service API with authenticated session scraping for the ubboard notice/Q&A boards.

Mounts a headless, low-memory browser for agents with a text-first tool interface, enabling navigation, semantic tree/markdown extraction, structured-data scraping, screenshots, form interaction, and session capture. Reads and interactions are returned as semantic trees, markdown, or CSS-selector JSON rather than pixels, which is cheaper for a model to reason over.