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Provides a Model Context Protocol server implementation for managing tasks, documents, and workspaces in Dart.
Enables LLMs to execute shell commands and receive their output.
Provides semantic, image, and cross-modal search functionalities.
Retrieves clipboard content, currently supporting image content on MacOS.
Demonstrates Semantic Kernel integration with Model Context Protocol in a Windows Forms application.
Provides example implementations of Model Context Protocol (MCP) servers for use with Cursor IDE, enabling enhanced AI capabilities with custom tools and data sources.
Bridges Claude and Prometheus, enabling interaction with Prometheus metrics and data through the Model Context Protocol (MCP).
Provides a Model Context Protocol (MCP) implementation to access and utilize the ZEN University syllabus content.
Enables real-time, human-to-human communication using the Model Context Protocol (MCP) by repurposing its tool-calling mechanism.
Connects Gemini CLI with a CoinGecko API server, providing access to a comprehensive suite of cryptocurrency data tools.
Converts website feedback and bug reports into actionable, context-enriched developer tasks for AI coding tools.
Provides an interactive chess game experience through a Model Context Protocol server.
Empower AI assistants to create, modify, and manage database diagrams programmatically through a WebSocket API.
Empowers AI to present choices and facilitates user selection through an interactive interface, returning the results to the AI.
Extracts the essential structure from large command outputs, returning only the schema to AI agents to optimize context and token usage.
Provides LLMs visual access to bare metal server consoles via iKVM/IPMI for AI-powered debugging and monitoring through screenshot capture.
Processes HTML and JavaScript, empowering LLM agents to interact with web content, render layouts, and execute scripts.
Dynamically generates executable tools for AI agents and MCP clients from any OpenAPI 3.x specification, enabling direct interaction with APIs.
Enables AI agents to conduct real user interviews via voice calls and generate structured insights like themes and verbatim quotes.
Integrates VictoriaTraces instances with the Model Context Protocol, enabling AI-powered interaction with distributed tracing data and embedded documentation.
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