Turn your app idea into IA, wireframes, PRD, style guides, and dev specs for coding agents.

Tribunal Kit is the governance layer for AI coding agents that stops AI hallucinations and npm ghost packages before they hit disk. Works with Cursor, Windsurf, Claude Code, and Aider.

Read, write, search, and surgically edit Obsidian vault notes, tags, and frontmatter via MCP. STDIO or Streamable HTTP.

Agent-native TypeScript framework for building MCP servers.

A local bridge for bidirectional collaboration between Claude Code and Codex. 连接 Claude Code 与 Codex 的本地实时协作桥接工具。

Open-source control plane for your AI agents. Connect tools, hire agents, track every token and dollar

The fullstack TypeScript framework for MCP and APIs — write one action, serve HTTP, WebSocket, CLI, background tasks, and MCP tools.

A markdown editor — and the bridge to your LLM. Local-first, MIT, ~15 MB. Bundled MCP server lets Claude Code / Codex / Cursor drive your vault directly. 14 AI providers BYOK.

Enables AI coding agents across supported harnesses to run a structured multi-agent workflow with persistent memory, squad roles, and bundled skills through MCP tools.

Enables agents to submit authorized state bundles for free staging dry-run previews that deterministically consolidate memories, plans, tool schemas, and logs over MCP, reporting what stays active, what moves to archive, and why.

🛡️ BLA (Blind LLM Agents) — Adversarial defense shield that protects binaries, Electron apps, JS bundles, Python, and WebAssembly against AI reverse-engineering agents like REA. Poison -> Exhaust -> Hallucinate.

Exposes MCP tools that compute longevity and metabolic metrics (autophagy index, GKI, MAGE), cardio-renal biomarkers (BUN/creatinine ratio, cardiac output and TPR, nocturnal BP dipping), chronobiology estimates (DLMO, melanopic lux, caffeine clearance), plus neuro-recovery and biomechanics scores. Runs as a zero-dependency Python JSON-RPC 2.0 stdio server so any MCP-compatible client can query these physiological domain calculators.

Persistent memory for AI agents: keyed facts, a wake bundle each session, one memory in every model.

Shared memory for teams and their AI agents: Markdown concepts with typed links in shared bundles.