An Agent Skill and Dify plugin to transform Markdown to files of DOCX, PPTX, XLSX, PNG, PDF, HTML, MD, CSV, JSON, XML.

Turn scattered knowledge, operational data, and history into source-linked context that your agents can inspect, explain, and reuse.

Build click-through, animated system architecture diagrams as a single HTML file. Drop it into a workshop, design review, or onboarding doc and let people watch the data flow instead of reading static boxes-and-arrows.

Network Sketcher is an AI-ready network design tool with Local MCP, Online, and Offline editions for creating network designs and exporting PowerPoint diagrams and Excel-based configuration data.

🐚 Python-powered shell. Full-featured, cross-platform and AI-friendly.

Knowhere extracts, parses, and outputs structured chunks ready for AI Agents and RAG.

A curated, multilingual library of 182 installable AI agent skills for end-to-end academic research—spanning literature discovery, scientific writing, grant development, bioinformatics, drug discovery, clinical research, machine learning, and data analysis.

Save or export your private and public Slack messages, threads, files, and users locally without admin privileges.

Model Context Protocol (MCP) Server for Graphlit Platform

The AI-native technical SEO crawler. Open-source MCP server for Claude / Cursor / Codex — 37 tools, 50+ checks, unlimited pages, WAF detection, ephemeral by design. Built on LibreCrawl. MIT.

24 cross-platform agent skills for Claude Code, Cursor, Codex & Gemini CLI — databases, messaging, research, TTS, DevOps, and Google Workspace

Universal SEO skill for Claude Code. 25 sub-skills + 18 sub-agents covering technical SEO, E-E-A-T, schema, GEO/AEO, backlinks, local SEO, maps intelligence, semantic clustering, e-commerce SEO, international SEO, Google APIs, and PDF/Excel reporting. Optional DataForSEO, Firecrawl, and Banana extensions.

A practical governance framework for organizations adopting the Model Context Protocol (MCP), the open standard that lets AI agents connect to external tools, data sources, and systems.

Skills for Syncfusion .NET MAUI components. Enable AI-assisted development with comprehensive documentation, code examples, and best practices for 100+ UI controls including DataGrid, Charts, Scheduler, and more.

Project memory for coding agents and humans: the reasoning behind a codebase as Markdown in the repo, versioned by Git, so nothing rejected is proposed twice. No database, no daemon, no account.

Agent skills for LandingAI's Agentic Document Extraction (ADE) — production-ready document AI for agentic coding assistants

🧠 Self-hosted, privacy-first MCP server for long-term AI memory — save, search & summarize Claude/ChatGPT chat history locally. No cloud, no database.

TypeScript Model Context Protocol (MCP) server boilerplate providing IP lookup tools/resources. Includes CLI support and extensible structure for connecting AI systems (LLMs) to external data sources like ip-api.com. Ideal template for creating new MCP integrations via Node.js.

HeyClaude is a curated registry and distribution surface for Claude and AI-workflow assets: agents, MCP servers, skills, commands, hooks, rules, guides, tools, jobs, Raycast feeds, static data exports, and an npm MCP package.

A PostgreSQL-backed archive generator that creates browsable HTML archives from link aggregator platforms including Reddit, Voat, and Ruqqus.

A Model Context Protocol (MCP) server implementation that integrates with the Nutrient Document Web Service (DWS) Processor API, providing powerful PDF processing capabilities for AI assistants.

Python, LlamaIndex, LangChain, 15 Property Graph, 4 RDF , 10 Vector, OpenSearch, Elasticsearch, Alfresco, Nuxeo DBs. 14 data sources (10 auto-sync), KG auto-building, Ontologies, LLMs, Docling, LlamaParse, LiteParse, GraphRAG, RAG, Hybrid Search, AI Chat. TypeScript React, Vue, Angular frontends, REST, MCP Server. Options: Langflow, CocoIndex

Power BI CLI - semantic models (.NET TOM) and PBIR reports for token-efficient AI agent usage, built for Claude Code

Git-native persistent memory for AI coding agents. Implements Google OKF v0.2 with sub-300µs in-memory BM25 search, embedded MCP server, and progressive disclosure. Slashes token bloat by 80% with zero external databases or dependencies. Built in pure Go.