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Run Wordware apps locally to integrate AI flows into a local development environment.
Executes server-side cursor operations for backlog management.
Provides a standardized template for building Model Context Protocol (MCP) servers with TypeScript/Node.js.
Connects to SAP Ariba Source data, making it accessible to Large Language Models (LLMs) through the Model Context Protocol (MCP) using CData JDBC Drivers.
Provides an unofficial MCP server for the Radio-T website API, enabling programmatic access to its content.
Provides real-time and scheduled bus information for Montevideo's public transportation system, enabling users to query schedules, routes, and arrival times.
Demonstrates Model Context Protocol (MCP) implementation with a Go-based host orchestrating services from both Go and Python servers.
Converts Markdown formatted text into high-quality images, offering multiple rendering backends and extensive customization.
Integrates Network School Luma calendar events and wiki resources with Claude Desktop, enabling natural language access to event schedules and important information.
Provides an MCP server for generating random numbers, performing statistical analysis, and managing data through client applications like Claude Desktop and Claude Code.
Integrates E2B with Claude AI Desktop to execute code in secure cloud sandbox environments.
Provides real-time and historical cryptocurrency market data from major exchanges via a Python-based Model Context Protocol server.
Automates Microsoft Office document processing using natural language commands via the Model Context Protocol.
Connects AI assistants to the Gamma API, enabling them to generate presentations and documents.
Exposes existing REST APIs as MCP servers with zero-code configuration.
Enables interaction with remote servers using the Telnet protocol, managing connections and data exchange programmatically.
Automates system tasks and provides advanced debugging capabilities for AI assistants.
Provides AI assistants with persistent memory across sessions by storing project context, decisions, and progress in structured markdown files.
Orchestrates multi-agent AI to streamline music production, featuring semantic sample search, MIDI generation, stem separation, and DAW control.
Enables natural language interaction with Jira for querying, creating, and updating issues, projects, and users through Model Context Protocol clients.
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