Ingest text and Plex items into a RAG vector database.
npx skills add https://github.com/MichaelYagi/mcp_a2a --skill rag-ingestion
Please help me install this Agent Skill. Skill: rag_ingestion Source: https://github.com/MichaelYagi/mcp_a2a/tree/main/servers/rag/skills/rag_ingestion Command: npx skills add https://github.com/MichaelYagi/mcp_a2a --skill rag-ingestion
Ingesting text and Plex items into a RAG vector database is tedious when done manually, hindering timely content indexing and retrieval.
To ingest a new article or media item, run rag_ingestion with the appropriate input, for example: rag_ingestion --text "Meeting notes" rag_ingestion --plex_batch /path/to/plex_export.json
High-intent search queries and answers about installing and using this skill.
You can ingest text into a RAG vector database by running the ingestion command with your raw text input. This adds the content directly to the RAG store, making it immediately searchable for retrieval.
Batch ingestion for Plex items is the process of adding multiple media entries into the RAG vector database simultaneously. This bulk operation updates the vector index for expanded searchable knowledge.
To reset subtitles for Plex items missing text data, you run a dedicated subtitle reset routine. This re-scans the specified items to fetch missing subtitles and keeps the embeddings fresh.
Yes, you can update the vector index for multiple Plex items at once using the batch ingestion feature. It processes multiple items in a single operation to expand the searchable knowledge base.
You need the rag_add_tool dependency to add content to the RAG index. The ingestion process relies on this tool to add content and update the vector database accordingly for retrieval.
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