moss_docs.json

[
  {
    "id": "moss-overview",
    "text": "Moss is a real-time semantic search runtime built for conversational AI. It returns results in under 10 milliseconds so voice agents can ground responses without blowing their latency budget.",
    "metadata": { "section": "overview" }
  },
  {
    "id": "agora-integration",
    "text": "Moss integrates with Agora Conversational AI by exposing a single MCP tool, search_knowledge_base, over streamable HTTP. Agora's orchestrator calls this tool during a conversation whenever the LLM decides to search.",
    "metadata": { "section": "integrations" }
  },
  {
    "id": "hybrid-search",
    "text": "Moss supports hybrid search: a tunable alpha parameter controls the blend between dense vector similarity and sparse keyword matching. Higher alpha means more weight on dense embeddings.",
    "metadata": { "section": "features" }
  }
]