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Enables interaction with the Garmin Connect API to manage user data.
Provides a standardized interface for data preprocessing, transformation, and analysis tasks within the Model Context Protocol ecosystem.
Demonstrates how to set up a Model Context Protocol (MCP) server and client using Server-Sent Events (SSE) for LLM prompting.
Connect large language models to Taroify for direct retrieval of component and API data from documentation.
Manages and automates interactions with Nature Remo devices through an MCP server.
Automates git commits on behalf of AI, enabling tracking of AI contributions in a codebase.
Enables AI assistants to perform DNS and WHOIS queries via local resolvers and remote DNS-over-HTTPS services.
Connects AI systems to the Stockfish chess engine via the Model Context Protocol.
Streamlines interaction with log files through a CLI and MCP server, aiding in debugging and monitoring.
Turns scattered AI conversations into persistent, searchable knowledge by capturing insights from any AI session and making them available across all your tools.
Connects AI Desktop Apps with Revit, enabling AI to inspect and select elements based on model feedback.
Provides an MCP server for HomeyPro home automation systems, enabling paginated access and comprehensive control over devices, zones, and flows.
Facilitates seamless interaction with the Camunda 7 Community Edition Engine for workflow automation and process management.
Provides an MCP server interface, enabling large language models to interact with Hydrolix clusters for executing SQL queries and introspecting database schemas.
Generates images using Google's Gemini API, integrating advanced image generation capabilities with various AI models via an MCP server.
Provides secure access to SvelteKit and Tailwind CSS documentation and code snippets to assist developers in building applications.
Builds a complete Model Context Protocol (MCP) server with STDIO transport for Claude Desktop, integrating with Microsoft Dynamics 365 Business Central.
Provides access to local Bevy examples and source code inspection for Bevy projects.
Exposes Flowbite-Svelte documentation and component information to large language models via Model Context Protocol (MCP).
Bridges AI assistants to local development environments, enabling agentic coding by adhering to the Model Context Protocol.
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