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    A local MCP server that routes QA reviews through deterministic profiles and risk-based escalation while keeping source evidence and final decisions with the host.
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    MIT
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    A machine-enforced workflow protocol for AI coding agents that eliminates false progress. Tasks require verifiable evidence to close, while decisions, assumptions, and open questions persist in a versioned reasoning graph for seamless agent handoffs. Designed to keep deep, long-running projects coherent across sessions, agents, and months.
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    AGPL 3.0
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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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    406
    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.
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    MIT
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    Enables AI coding agents to get one independent reviewer that first reasons about a problem without seeing the proposed solution, then compares it against the revealed proposal and returns a compact verdict (KEEP/MODIFY/REPLACE/INSUFFICIENT_EVIDENCE) with risks, an alternative, and a falsification probe before committing to expensive decisions.
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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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    Least-privilege compiler and MCP gateway for AI agents: run your agent in record-only mode, compile the smallest policy it actually needs from its real tool calls, enforce it at the gateway (deny > approve > allow), and keep a SHA-256 hash-chained audit of every call that verifies offline.
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    93 npm
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    Apache 2.0
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    Enables agents to discover, suggest, bind, and read local SKILL.md skills via MCP, while enforcing a maximum of three bound skills and a token budget to keep context small.
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    11 npm
    MIT