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"Latest Updates on macOS Compatibility with Electron" matching MCP servers:

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    A collection of MCP servers for Apple macOS apps (Mail, Contacts, Notes, Memory, Messages, Calendar, Reminders) enabling AI assistants to read, search, create, and update data via JXA, SQLite, and EventKit.
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    MIT
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    On Board is a local MCP server that gives multiple AI agents and IDEs a shared project memory, ticket queue, and handoff history, so agents can seamlessly continue each other's work. It supports agent-to-agent wake events, enabling autonomous workflows like reject-fix-resubmit cycles without human relay.
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    Apache 2.0
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    Enables chat with multiple LLM providers (OpenAI and Anthropic) while maintaining persistent conversation memory. Provides extensible tool framework for various operations including echo functionality and conversation storage/retrieval.
    MIT
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    Connects Bear Notes to AI assistants using semantic search and RAG (Retrieval-Augmented Generation), allowing AI systems to access and understand your personal knowledge base through meaningful search rather than just keyword matching.
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    MIT
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    Provides full access to Hookmark on macOS, enabling users to create and manage bidirectional links between files, URLs, emails, and notes. It supports searching bookmarks, connecting items, and retrieving links from active applications through natural language.
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    MIT
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    MCP server for local-first agent handoff: enables AI sessions to publish curated context, list/read updates, route handoffs to specialists, and advance per-consumer cursors, with SQLite persistence and no shell or network access.
    8
    Apache 2.0
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    A comprehensive Model Context Protocol (MCP) server for Obsidian on macOS. It provides extensive tools for interacting with Obsidian vaults, notes, and application state through AppleScript, URI schemes, and direct file system access.
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    MIT
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    SourceSage is an MCP (Model Context Protocol) server that efficiently memorizes key aspects of a codebase—logic, style, and standards—while allowing dynamic updates and fast retrieval. It's designed to be language-agnostic, leveraging the LLM's understanding of code across multiple languages.
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