A local-first MCP server for manually building, inspecting, and saving directed acyclic graphs (DAGs) for custom days, with optional evidence summaries from Home Assistant.
Enables AI assistants to create, edit, and export flowcharts through a local web-based editor with visual drag-and-drop, real-time sync, and 14 MCP tools for full node/edge CRUD.
A persistent, self-revising hypothesis DAG for agentic R&D, exposed as an MCP server. It enables agents to structure working knowledge as a directed acyclic graph of hypotheses, with automatic write-back belief revision and cascading pruning based on evidence.
A local, model-independent DAG task coordinator for AI coding agents, with a static visual UI, validated state machine, resumable JSON progress, and MCP tools.
A local, auditable multi-model workflow engine that lets you define YAML graphs for orchestrating LLM agents across vendors, with MCP tools for validation, dry-runs, execution, and human approval, all fully observable in a local web interface.