agents offers a single configuration point to manage MCP servers, skills, and instructions across various AI tools such as Codex, Claude, and Gemini. Simplifying onboarding and updates, this solution mitigates the hassle of maintained multiple config files while ensuring all tools are seamlessly synchronized.
The agents project offers a unified configuration management solution designed to streamline multi-LLM development. With this tool, developers can simplify their interactions with a variety of AI platforms, including Codex, Claude, Cursor, and Gemini, through a single source of truth that enhances organization and reduces complexity.
.agents/ directory to manage all Multi-Channel Protocol (MCP) servers, skills, and instructions across different tools effortlessly..agents/
├── agents.json → All your MCP servers
├── local.json → Your secrets (gitignored)
└── skills/ → Reusable team workflows
| Tool | MCP Integration | Skills | Instructions |
|---|---|---|---|
| Codex | ✅ | ✅ | ✅ |
| Claude Code | ✅ | ✅ | ✅ |
| Gemini CLI | ✅ | ✅ | ✅ |
| Cursor | ✅ | ✅ | ✅ |
| Copilot | ✅ | ⏳ | ✅ |
| Antigravity | ✅ | ✅ | ✅ |
| Command | Description |
|---|---|
agents start | Launch the interactive setup wizard. |
agents sync | Update all tools with the latest config. |
agents mcp add <url> | Add a new MCP server URL. |
agents mcp list | Display all configured MCP servers. |
agents doctor | Diagnose configuration issues. |
agents status | Check the connection status of all tools. |
agents watch | Enable real-time synchronization of changes. |
.agents/agents.json file or utilize the CLI for modifications.agents tool reads the configuration and automatically generates the specific config files needed for each integrated tool.Simply install the npm package, initialize the agents setup in your project directory, and run the synchronization command to keep everything up-to-date. This ensures that all configurations are consistently aligned across various platforms, minimizing the risks of errors due to outdated or mismatched configurations.
If issues arise or suggestions for improvements come to mind, users are encouraged to engage with the community by reporting bugs or participating in discussions to enhance the project further.
This repository is constructed to assist AI developers in navigating the complexities of multi-LLM environments efficiently, providing them with tools necessary for collaborative and successful developments.
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