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Enables AI assistants to manage Google Calendar events through natural language interactions.
Summarizes chat messages based on user queries.
Enables local execution of commands and file operations via the Model Context Protocol (MCP) for use with tools like the Claude Desktop App.
Automates machine learning workflows, from data analysis to model deployment, with Model Context Protocol integration.
Generates AI-powered meeting summaries and answers questions based on transcripts, delivering high-quality Markdown reports.
Enables AI assistants to control a browser through a set of tools, allowing them to perform web automation tasks like navigation, typing, clicking, and taking screenshots.
Transforms codebases into intelligent embeddings, enabling semantic code search for large language models and multi-agent systems.
Enables programmatic interaction with Google Drive files and Google Sheets.
Enables AI assistants to interact with Medium's content platform programmatically, offering capabilities to manage articles, drafts, and user profiles.
Manages tasks within Claude Desktop, offering capabilities to add, list, complete, and delete entries.
Intelligently routes tasks to multiple AI agents based on their strengths or user preferences, with auto-fallback on failure.
Empowers AI clients to interact with and control Linux GNOME desktop environments, automating various system and application tasks.
Facilitates natural language interaction between AI assistants and the Inflectra Spira platform for managing software development and testing artifacts.
Provides a versatile server for rolling dice with standard notation, character stat generation, coin flips, and random selections.
Provides a Model Context Protocol server for comprehensive interaction with the Coda.io API.
Enables AI agents to create, manage, and execute blockchain automation workflows.
Enables AI assistants to search and discover vacation rental properties in La Palma, Canary Islands, through natural conversation.
Automate Vector CANoe operations for automotive network testing and simulation using AI agents.
Delivers real-time pollen level alerts and practical tips for managing hayfever symptoms.
Establishes a persistent intelligence layer for LLM-powered agents, enabling memory and learned patterns to compound across development sessions.
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