1
Add it to Claude Code
claude mcp add godot-rag -- python "<path to the server script 'main.py'>" -d "<path to the chroma_db on your computer>" -c "<name of the collection in the chroma_db>"2
Make your agent remember this setup
godot-rag's config, env vars, and the gotchas you hit — recalled in every future Claude Code, Cursor, and Codex session.
npx conare@latestFree · one command · indexes the sessions already on disk. Set up in the browser instead →
What it does
- Retrieval-Augmented Generation for Godot engine documentation
- Integration with ChromaDB for vector storage
- Supports custom vector collections for different documentation versions
- Includes scripts for downloading, converting, and chunking Godot docs
Environment Variables
OPENAI_API_KEYRequired if using the API-based vectorization or model featuresTry it
→How do I implement a state machine in Godot 4 using GDScript?
→Explain the difference between Area2D and RigidBody2D based on the documentation.
→What are the best practices for optimizing performance in Godot 3D scenes?
→Find the documentation for handling input events in Godot.
Original README from weekitmo/mcp_godot_rag
A MCP server for Godot RAG
This MCP server is used to provide Godot documentation to the Godot RAG model.
Screenshot
Before using
After using
MCP server config
{
"mcpServers": {
"godot-rag": {
"command": "python",
"args": [
"",
"-d",
"",
"-c",
"<name of the collection in the chroma_db>"
]
}
}
}
Setup
uv venv --python 3.12
source ./.venv/bin/activate
uv sync
cp .env.example .env.local
Initiation steps
# clone godot docs
python download_godot_docs.py
# convert rst to markdown
python convert_rst2md.py
# chunk markdown files
python chunker.py -i artifacts
# create vector database
python vectorizer.py -i artifacts/chunks/artifacts_chunks_SZ_400_O_20.jsonl
# python vectorizer_api.py -i artifacts/chunks/artifacts_chunks_SZ_400_O_20.jsonl -m BAAI/bge-m3
# start mcp server
python main.py -d artifacts/vector_stores/chroma_db -c artifacts_chunks_SZ_400_O_20_all-MiniLM-L6-v2
# python main_with_api.py -d artifacts/vector_stores/chroma_db -c artifacts_chunks_SZ_400_O_20_BAAI-bge-m3 -k <your openai api key>
Debug
npx @modelcontextprotocol/inspector \
uv \
--directory . \
run \
main.py \
--chromadb-path artifacts/vector_stores/chroma_db \
--collection-name artifacts_chunks_SZ_400_O_20_all-MiniLM-L6-v2
Use Another Model
Other
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