MCP server that equips AI agents with dev workflow tools including GitHub project management, conventional commits, visual regression testing, Jira/Confluence integration, and a persistent memory knowledge graph.
MCP server that enables AI agents to run a deterministic orchestration loop with decomposition, subagent execution, and review feedback across multiple LLM backends.
MCP server that enables agents to dynamically switch between multiple AI models (OpenAI, Anthropic, Google, etc.) with unified protocol-driven configuration and capability discovery.
An MCP server that allows a planning agent to delegate tasks to executor agents (e.g., Claude Code, Aider) with bi-directional communication and real-time log streaming.
MCP server that gives AI coding assistants persistent memory, structural code graph analysis, and safe multi-agent coordination, enabling them to answer architectural questions, track decisions across sessions, and coordinate safely in multi-agent workflows.
