What models does Godot RAG support?
It supports all-MiniLM-L6-v2, bge-m3, and bge-large-zh-v1.5 sentence transformer models.
@weekitmo
基本信息
This MCP server is used to provide Godot documentation to the Godot RAG model.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"mcp_godot_rag": {
"command": "uv",
"args": [
"venv",
"--python",
"3.12"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
Godot RAG is an MCP server that provides Godot documentation to a Godot RAG (Retrieval-Augmented Generation) model. It is intended for developers using AI assistants to access Godot documentation.
Configure the MCP client with the server command python and arguments pointing to main.py, the chroma_db path (-d), and the collection name (-c). Run the setup steps: clone Godot docs, convert RST to Markdown, chunk the files, create a vector database, then start the server.
It supports all-MiniLM-L6-v2, bge-m3, and bge-large-zh-v1.5 sentence transformer models.
Run `python download_godot_docs.py`, then `convert_rst2md.py`, then `chunker.py`, then `vectorizer.py` with the appropriate arguments.
The server requires Python 3.12, uv for virtual environment, and dependencies from `uv sync`.
The chroma_db is stored at a path specified by the `-d` argument when starting the server.
Use `npx @modelcontextprotocol/inspector` with the `uv run main.py` command and the chromadb path and collection name arguments.

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