AI DevKit offers a local control plane for multi-agent coding teams
AI DevKit is a local control plane that lets developers run Claude Code, Codex, Cursor, Gemini CLI, opencode, and Pi as a coordinated team through shared config, a unified console, local memory, cross-agent messaging, and verification gates.
Score breakdown
AI DevKit addresses the orchestration gap that emerges when developers run multiple coding agents simultaneously — shared config, memory, messaging, and verification are handled at the control-plane level rather than manually across scattered terminal sessions.
- 01AI DevKit is a local control plane for coordinating multiple AI coding agents from one project-local setup.
- 02Supported agents include Claude Code, Codex, Cursor, Gemini CLI, opencode, and Pi.
- 03A single `.ai-devkit.json` file reconciles configuration across all agents in a project.
AI DevKit describes itself as a local control plane designed for developers who are already operating more than one AI coding agent simultaneously. Rather than replacing any individual agent, it sits above tools like Claude Code, Codex, Cursor, Gemini CLI, opencode, and Pi, providing the shared infrastructure they lack out of the box: a single project-local `.ai-devkit.json` config that reconciles each agent's rules, and an `agent console` command that surfaces all running sessions in one place instead of scattered terminal tabs.
Cross-agent communication is handled by `agent send`, which pipes prompts, logs, test output, or review tasks to a specific agent by ID or to a named agent group — replacing manual copy-pasting of context.
The toolkit addresses four specific operational pain points. Cross-agent communication is handled by `agent send`, which pipes prompts, logs, test output, or review tasks to a specific agent by ID or to a named agent group — replacing manual copy-pasting of context. A local SQLite database provides persistent memory so agents can search for stored conventions, past decisions, and reusable fixes rather than requiring that context to be re-injected into every prompt. Finally, a `verify` feature introduces verification gates that require fresh build or test evidence before a task is considered complete, rather than accepting an agent's self-reported "done." The project is released under the MIT License and is available on GitHub.
Key facts
- 01AI DevKit is a local control plane for coordinating multiple AI coding agents from one project-local setup.
- 02Supported agents include Claude Code, Codex, Cursor, Gemini CLI, opencode, and Pi.
- 03A single `.ai-devkit.json` file reconciles configuration across all agents in a project.
- 04The `agent send` command routes prompts, logs, test output, and review tasks to specific agents or agent groups.
- 05A local SQLite store provides agents with searchable memory for conventions, decisions, and reusable fixes.
- 06The `verify` feature requires fresh build or test output as proof before a task is marked done.
- 07The project is MIT-licensed and initializes with `npx ai-devkit@latest init`.
Topics
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