BM25 search + tree navigation over markdown docs for AI agents. No embeddings, no LLM calls.
Agentic document retrieval over markdown — BM25 search + tree navigation via MCP. Give an AI agent structured access to your markdown docs: it searches with BM25, reads the outline, reasons about which sections matter, and retrieves only what it needs. No vector DB, no embeddings, no LLM calls at index time. Standard RAG gives agents a bag of loosely relevant paragraphs. This gives them a table…
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list_documentsNo description publishedThis tool published no description. Forge does not invent one.
search_documentsNo description publishedThis tool published no description. Forge does not invent one.
get_treeNo description publishedThis tool published no description. Forge does not invent one.
get_node_contentNo description publishedThis tool published no description. Forge does not invent one.
navigate_treeNo description publishedThis tool published no description. Forge does not invent one.
0 of 5 tools published a description.
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Agentic document retrieval over markdown — BM25 search + tree navigation via MCP. Give an AI agent structured access to your markdown docs: it searches with BM25, reads the outline, reasons about which sections matter, and retrieves only what it needs. No vector DB, no embeddings, no LLM calls at index time. Standard RAG gives agents a bag of loosely relevant paragraphs. This gives them a table of contents they can reason over, plus a search engine that actually ranks by relevance. Context…
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