Browse the catalog

Real-time duplex voice call sentiment interceptor & script adapter (Dograh style)

Tagless personal memory stream & timeline extractor (monolog style)

This skill defines and applies **6 universal quality gateways** for typical application projects that include:.

Redis MCP Server provides a Spring Boot implementation that enables AI tools to interact with Redis databases through a set of standardized operations. Developed by yue9527, it offers key-value operations (set, get, delete) and pattern-based key listing with optional expiration time settings. The server connects to Redis using the Lettuce client, exposes its functionality through Server-Sent Events (SSE), and can be easily configured to work with tools like Cursor. It's particularly useful for developers who need to manage Redis data stores directly from their AI assistants without switching contexts.

Provides AI agents with access to a comprehensive database of 200+ Next.js documentation URLs for intelligent document selection and retrieval. Enables Claude and other AI assistants to analyze user queries and recommend the most relevant Next.js documentation pages.

Production-grade high-volume voice agent orchestrator with warm human transfer & CRM telephony sync (Retell style)

Provides tools for interacting with Interactive Brokers Gateway to access market data, account summaries, and portfolio positions. It enables users to perform contract lookups, retrieve historical OHLCV bars, and view real-time quotes through natural language interfaces.

Generate diverse creative illustrations via OpenAI Images API.

URL intelligence for AI agents. One URL in, structured security and data quality signals out across 7 dimensions. 13 tools, risk score 0-100 with 23 configurable weights.

A Model Context Protocol (MCP) server that demonstrates mathematical capabilities through a LangChain integration, allowing clients to perform math operations via the MCP protocol.

AutoHotkey Computer Use exposes Windows desktop automation through an MCP interface, using AutoHotkey v2 and the Windows UI Automation framework for token-efficient interaction. AI agents can control desktop applications, automate GUI workflows, and perform computer use tasks without screenshot-heavy approaches.

AI commerce platform — WooCommerce store products, flights, tours, activities and local transport via MCP. Search, availability and booking tools. No auth for public endpoint.

MCP server: phonetic encoding (Soundex, Metaphone).

Phone-camera + Bluetooth remote control for any computer, exposed as an MCP server for Claude, Cursor and other AI assistants

Production-ready NestJS boilerplate with JWT auth, PostgreSQL/Prisma, AWS S3/SES, Bull/Redis queues, Docker/K8s support, and MCP integration for AI capabilities

Bilibili-mcp-server is a Go-based MCP server that provides a bridge to the Bilibili API, enabling AI assistants to interact with the popular Chinese video-sharing platform. Developed by DnullP, this implementation offers tools for retrieving user profile information, listing followed accounts, and finding videos through both v1 (tools) and v2 (resource) interfaces. The server requires user authentication via cookies stored in a configuration file and leverages the CuteReimu/bilibili Go library for API interactions. It can be compiled for both Windows and Linux environments, making it useful for applications that need to access Bilibili account data or content discovery without direct API integration.

A service that lets readers chat with fictional characters from novels, where the AI adopts the character's personality, memory, and knowledge for immersive roleplay.

MCP server for Fizzy (Kanban tool by 37signals) that enables AI assistants to read and manage boards, cards, columns, tags, comments, and more.

GenPark AI Agent Skill - Information entropy and lexical diversity turn pruner stripping conversational noise while preserving core user intent.

MCP Memory Server provides long-term memory capabilities for AI assistants using PostgreSQL with pgvector for efficient vector similarity search. The implementation uses the Xenova/all-MiniLM-L6-v2 model to automatically generate embeddings for stored memories, enabling semantic search across different memory types. It exposes tools for creating, searching, and listing memories with support for tagging, confidence scoring, and filtering, making it particularly valuable for AI assistants that need to maintain context and recall information across conversations without losing important details.