Enables AI agents to manage tasks on a local-first board via MCP, exposing task creation, updates, and queries through a thin adapter over the REST service.
A self-hosted backlog tracker with priority scoring and an MCP server, enabling AI agents to autonomously pull, work on, and update tasks via JSON-RPC tools.
A local Model Context Protocol server providing backend tools for AI agents to manage projects and tasks with persistent storage in SQLite, enabling structured tracking of project tasks with dependencies, priorities, and statuses.
Enables AI clients to create and manage tasks via a local REST API by converting natural language into HTTP requests through the Model Context Protocol.
Task management API for AI agents. Create, delegate, and track tasks with agent identity, delegation chains, lifecycle webhooks, and persistent context.
Enables AI agents to manage tasks through a structured lifecycle (todo, in_progress, ai_testing, manual_testing, deployment, completed) with human approval gates, providing a single-user task management system with CLI, REST API, and live updates.