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    An MCP project that orchestrates coffee orders by coordinating a Barista server and machine servers (grinder, brew unit, steamer, dispenser) through an LLM.
    7
    MIT
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    Enables multiple AI coding-agent sessions on one machine to hand tasks to each other and get results back through a shared local folder of JSON messages, with no cloud, database, or network service. Supports direct messages, broadcasts, blocking receive, and an optional headless worker that picks up, runs, and auto-replies to tasks.
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    MIT
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    A Model Context Protocol (MCP) server that provides intelligent search capabilities for discovering relevant Claude Agent Skills using vector embeddings and semantic similarity. This server implements the same progressive disclosure architecture that Anthropic describes in their Agent Skills enginee
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    411
    Apache 2.0
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    Lets separate coding-agent sessions coordinate through a shared, role-addressed mailbox instead of a human relaying every message, over a single local SQLite file or a hosted server with many isolated channels. Messages can be sent as tracked obligations that stay open until one side resolves and the other confirms, alongside threads, full-text search, work statuses, and an append-only versioned pin system where protected changes require recorded agreement from every declared role.
    41
    MIT
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    Enables AI coding agents from any vendor to resume a task from the exact stopping point without model calls, re-reading old sessions, or re-exploring the code, by merging host hooks, agent checkpoints, and Git deltas into one compact brief. It also guards credits outside the model with a prompt clarity gate, a loop guard, and configurable token profiles.
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    92 npm
    MIT
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    Enables Claude Code and other MCP clients to obtain fast, low-latency snap decisions — tool choice, option selection, and abstention when confidence is low — from a pluggable local decision engine such as Laya, Von, an Ollama chat model, or a custom provider. Engines can be swapped without changing the stable tools the client sees, with validation, per-attempt timeouts, confidence thresholds, and fallback chains handled by the server.
    3
    Apache 2.0
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    Enables AI agent hosts to exchange durable, local sender/receiver messages through a SQLite mailbox exposed as MCP tools (connect, send, receive, reply, ack, status, disconnect), so a coordinator can dispatch commands and an executor can return results without model polling while idle. A configured host wake adapter is still required to turn an incoming event into an Agent turn.
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    MIT
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    Discover which MCP servers can interact with real-world entities like restaurants, hotels, and salons by querying the Dock AI registry using domain names.
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    Enables AI agents to delegate scoped tasks across multiple providers like Codex, Claude Code, and Antigravity through a single local MCP server, with quota monitoring, notifications, and remote control via messaging apps.
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    Apache 2.0
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    Enables multiple coding agents (Claude Code, Codex, Cursor) to discover each other's sessions, search transcripts, ask questions, and handoff tasks through a shared MCP server.
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    4 npm
    MIT
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    A personal work twin for any AI agent. It briefs agents on the guidance you have confirmed, checks consequential actions against explicit, expiring grants and asks otherwise, and turns your corrections into lessons only you can confirm.
    12
    22 PyPI
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    Apache 2.0
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    Enables AI agents from different frameworks to communicate asynchronously via a persistent SQLite-backed bus, with doorbell wakeups for sub-second notifications and full message history.
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    MIT
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    MCP server that provides a live coordination layer for AI agents, including attributable handoffs, a shared event ledger, atomic work-claiming, and advisory file leases to prevent collisions.
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    AGPL 3.0
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    An AI personality collaboration tool based on Model Context Protocol (MCP) that enables users to summon and collaborate with multiple AI personas for intelligent analysis and problem-solving.
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    5 npm
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    MIT