Keepygaga RAG

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Keepygaga RAG is an independently installable Knowledge/RAG product in the Keepygaga family. It is a sibling of the Keepygaga core-memory product: each runs, ships, and evolves independently, and their only integration is parallel registration in an Agent host. Keepygaga RAG indexes authorized local Markdown and plain-text sources, combines SQLite FTS5 and LanceDB vector recall with reciprocal-rank fusion, and applies online reranking while preserving traceable source coordinates.

Project status: personal software in active development (pre-alpha). This repository is published for early testing and collaboration. Interfaces, data formats, and behavior may change without notice. There is no support, uptime, or compatibility commitment, and issues or pull requests may be handled at the maintainer's discretion.

Its only public MCP tool is raw search. When the MCP host registration ID is keepygaga_rag, the complete host tool name is mcp__keepygaga_rag__search. The MCP Server display name is Keepygaga RAG.

Requirements

• Python 3.12+
• A local directory containing Markdown or plain-text material
• Configured and user-authorized embedding and reranking APIs
• uv is recommended

Install and use

git clone https://github.com/TimWongUp/keepygaga-rag.git
cd keepygaga-rag
uv sync --extra dashboard
cp keepygaga-rag.example.toml keepygaga-rag.toml
uv run keepygaga-rag doctor
uv run python mcp_server.py
uv run keepygaga-rag dashboard
uv run keepygaga-rag indexer

The Dashboard listens on 127.0.0.1:8765 by default. Runtime overrides use KEEPYGAGA_RAG_CONFIG, KEEPYGAGA_RAG_DASHBOARD_PORT, and KEEPYGAGA_RAG_DASHBOARD_AUTO_CLOSE.

Safety boundaries

• Original files remain authoritative; indexes are rebuildable derived data.
• agents-memory/** and _context-backups/** are always excluded at every depth.
• Indexed text is sent only to the authorized embedding provider. Query text and candidate chunks are sent only to the authorized reranker.
• Provider, model, or source-scope changes require renewed user consent.
• Hybrid results locate sources; read the returned source file before treating a match as authoritative.

For the exact local/external data boundary, credential handling, and provider responsibilities, see Privacy and data flow.

Contributing and security

Contributions are welcome within the project's pre-alpha scope. Before opening an issue or pull request, read Contributing.

Do not report vulnerabilities in a public issue. Follow the private reporting instructions in Security.

License

MIT