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    An MCP server that extends AI coding assistants with deterministic, algorithmic capabilities such as code analysis, fault localization, and formal verification, enabling an autonomous engineering team within the IDE.
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    MIT
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    Orchestrates multiple Claude Code instances into a collaborative swarm for real-time task delegation, message exchange, and code snippet sharing. It features peer discovery, status tracking, and a centralized web dashboard to monitor coordinated activity across sessions.
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    MIT
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    Multi-agent swarm orchestrator for AI workflows. Exposes blackboard read/write, agent dispatch, permission gating (AuthGuardian), token budget enforcement (FederatedBudget), and audit log tools over MCP. Supports 14 AI framework adapters including LangChain, AutoGen, CrewAI, Codex, and A2A — mix any frameworks in one swarm with race-condition-safe shared state.(Traffic light for agents)
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    MIT
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    More than just a fully featured MCP server that lets AI agents manage Docker — containers, images, networks, volumes, swarm services, secrets, configs, nodes, plugins, etc., it helps you create workflows to easily manage your Docker environments.
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    MIT
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    Provides tools for AI agent persona management, safety verification, and efficient swarm memory synchronization across multiple agents. It enables users to search and install personas while utilizing a token-efficient Git-based workflow for maintaining shared project context.
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    MIT
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    Enables querying Swarmia's Export API for engineering metrics including pull request analytics, DORA metrics, investment balance, and effort reporting through an MCP interface.
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    MIT
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    A CLI and MCP server for managing skills across ~45 code CLI agents, with 18 tools for discovering, installing, enabling, and syncing skills in mid-session.
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    MIT
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    Exposes the Swarmia Export API as tools for AI assistants to query engineering metrics through natural language. It enables retrieval of DORA metrics, pull request cycle times, investment balances, and FTE effort reports.
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    MIT
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    A multi-agent collaboration platform that provides access to over 1,500 models from 68 providers via the Model Context Protocol. It enables users to assemble and coordinate specialized AI teams using advanced orchestration modes like swarm, debate, and hierarchical workflows.
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    2
    AGPL 3.0