Knowledge Rag vs Redm Mcp

R

search_knowledge

Hybrid search combining semantic search + BM25 keyword search with cross-encoder reranking. Read-only. No side effects. Args: query: Search query text (1–3 keywords recommended; phrase queries also work) max_results: Maximum number of results (default: 5, max: 20) category: Optional category filter — one of: security, ctf, logscale, development, general, redteam, blueteam. Call list_categories() first to see available categories and counts. hybrid_alpha: Balance between semantic and keyword search. 0.0 = keyword-only (best for exact technical terms like CVE IDs or tool names), 0.3 = balanced default, 1.0 = semantic-only (best for conceptual or natural-language queries). min_score: Minimum normalized relevance score (0.0–1.0) to include a result. Results scoring below this threshold are discarded. Default 0.0 returns all results. Use 0.2–0.4 to cut low-relevance noise. snippet_mode: When true (default), truncates content to ~500 characters at a natural break point and adds a content_length field with the original size. Use get_document() to fetch full content when needed. Set to false to return full chunk content. search_method: Dispatch selector (v4.8.2+). One of ``"auto"`` (router picks FTS5 fast-path for lexical queries when enabled, hybrid otherwise), ``"hybrid"`` (force hybrid path — kill switch for suspected router misclassification), or ``"fts5"`` (force FTS5 fast-path — debug/testing; errors out when the feature is disabled or the index is not ready). Default ``"auto"`` preserves pre-v4.8.2 behavior byte-for-byte when the fast-path is disabled in config. Returns: JSON string with results including content chunks, source filepath, relevance score, and search method used. Returns chunks, not full document content. Usage: Primary search tool — use for any topic or keyword lookup. Prefer search_similar() when you already have a reference document and want more like it. Prefer get_document() when you already know the exact filepath and need the full content.