Turns your intent and source facts into approval-ready Korean public-sector documents — reports, official letters, regulations, press releases, and slides — as HTML, PDF, HWPX, and PPTX. Everything runs locally so your documents never leave your machine; only formatting-rule fragments are fetched from a policy server.
This MCP server enables AI agents to search and retrieve exact, cited passages from a large corpus of public-domain books, including full-text search, book metadata, chapters, quotes, and 'ask book' Q&A. Payments are handled via x402 micropayments on Base.
Enables a shared persistent knowledge vault for Claude Desktop, allowing notes to be saved, retrieved, searched, updated, and deleted across Chat and Code tabs.
An MCP server that lets AI assistants add papers and books to your Zotero library by DOI, arXiv ID, or ISBN, and manage your collections, tags, and items.
A flexible memory system for AI applications that supports multiple LLM providers and can be used either as an MCP server or as a direct library integration, enabling autonomous memory management without explicit commands.
Enables secure, deny-by-default automation of Windows windows with per-action permissions, allowing observation, clicking, typing, and dragging on approved applications while verifying target identity and focus at runtime.
Provides instant, offline access to a curated intelligence database of 25 Solana/web3 earning platforms, with tools to search topics, retrieve detailed evidence notes, and view verdict, payout rail, and KYC gate statistics.
Enables searching and analyzing LinkedIn's public ad library for any company, including ad creatives, targeting, and competitive insights. Supports image and video analysis, company comparisons, and detailed ad lookups via natural language.
MCP server for the Mamba Labs Meta Ad Library Monitor actor on Apify. Find a company active Facebook and Instagram ads through the Meta Ad Library API.
Provides persistent local memory for any MCP-compatible AI agent, enabling agents to store, search, recall, forget, export, and manage preferences, rules, and facts with zero dependencies, no cloud, and no API keys.
A different approach from typical persistent-memory MCPs. Instead of a local
SQLite + embeddings store, the memory lives as plain files in a .ai-memory/
directory you commit to your repo (facts.jsonl, decisions/\*.md, gotchas.md).
Git is the sync layer — what one Claude/Cursor/Cline learns about a repo, the
next session (or a teammate's agent) picks up automatically.
5 MCP tools: get_rep