AI coding assistants have made it trivially easy for one person to "vibe code" a small internal app — a dashboard, a data lookup tool, a quick automation — in an afternoon. The catch is that it usually only runs on that person's laptop, so sharing it with a teammate means either rebuilding it properly with real hosting and auth, or just not sharing it at all. Toolchestrator is built specifically to remove that step: the tool keeps running exactly where it was built, and the hub gives teammates a browser-based window into it, without anyone migrating code or setting up servers. Technically, the connection from the local machine to the hub is outbound-only, so nothing has to be exposed or port-forwarded on the developer's network. Once connected, teammates get browser-based access with full app and terminal streaming, shared queryable data with field-level dependency tracking, and one-click execution of specific actions from a dashboard rather than needing to open the whole app. It also integrates with AI assistants through the Model Context Protocol (MCP), plus pipeline orchestration, change alerts, an activity audit trail, and granular per-person access controls — the governance layer that IT/security teams will care about once "shadow AI tools" start spreading informally across a company. Client libraries are open source (MIT) on PyPI and npm, though the hub itself is still in an early, free onboarding phase with commercial pricing not yet fixed.
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