Async MCP server for running long-running AI tasks with real-time progress monitoring, enabling users to start, monitor, and manage complex AI workflows across multiple models.
MCP server for task management, project knowledge, workspace trust, runner sandboxes, extension registry, and workflow prompts, enabling AI agents to manage tasks and collaborate locally.
An MCP server that enables asynchronous task submission and execution through a local worker daemon, decoupled from specific providers and models, with tasks continuing even after the client disconnects.
An MCP server that allows AI agents to publish real-world tasks, match workers, manage progress, and handle compliant payments via standardized tools and resources.