Enables AI agents and humans to collaboratively manage kanban boards and Markdown documentation via MCP tools, with stable item keys, revision-safe editing, and full audit trails.
Enables orchestration of autonomous coding agents (Claude Code, Cursor, etc.) through an objective-native planning board with hash-chained audit trail. Humans define outcomes, agents claim and execute tasks via MCP.
Enables multiple AI models to collaborate under a shared goal, architecture, plan, loops, sandbox, and acceptance criteria via a local-first MCP server.
Enables visual collaboration with an AI agent on a codebase through a shared drawing canvas, where hand-drawn diagrams are inferred as editable structure over MCP.