NotebookBrain MCP
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- AlicenseBqualityCmaintenanceEnables code agents to read, search (local BM25/grep or semantic), and reason over NotebookLM sources stored as Markdown with minimal context use, including outline-based section reading, cached stats, cited chat answers, and export to .md files. Read-only by default, with write and destructive operations requiring explicit opt-in and exact-title confirmation.23MIT
- FlicenseNot gradedqualityAmaintenanceEnables AI agents and MCP hosts to query locally indexed notes, docs, chat logs, and other files via hybrid vector/BM25 retrieval with section-level citations. Exposes tools, resources, and prompts for searching and asking over the indexed content.-
- FlicenseNot gradedqualityAmaintenanceEnables AI agents to search and query a local knowledge base of scattered notes and docs through hybrid vector plus BM25 retrieval with section-level citations, and to store, retract and explore durable memories, note links and agent harness memories. It also exposes note resources plus briefing, study-plan and contradiction-check prompts, all backed by a shared local index.-
- FlicenseNot gradedqualityAmaintenanceEnables AI agents to search and question a personal knowledge base of notes and documents through hybrid vector and BM25 retrieval, with section-level citations. It also lets agents store, retract, and explore durable memories, links, and indexing statistics across tools.-
- FlicenseNot gradedqualityAmaintenanceEnables AI agents to search scattered notes and docs with hybrid vector + BM25 retrieval, get cited answers with section-level references, and store, retract, or explore durable memories and note links. It also exposes index inspection/refresh along with note resources and briefing, study-plan, and contradiction-check prompts.-
- FlicenseNot gradedqualityAmaintenanceEnables AI hosts and agents to query locally indexed notes, docs, PDFs, chat logs, and other scattered files through hybrid vector and BM25 retrieval with section-level citations. It exposes tools, resources, and prompts for searching, asking questions, scoping by tags, traversing links, and reranking results.-
TDQS
Scored across 3 tools
Each tool has a distinct action and resource: add_source writes a source, list_sources enumerates sources, and ask queries the accumulated sources. There is no plausible overlap in agent selection.
add_source and list_sources follow a clear verb_noun snake_case convention, and ask is also snake_case but is a bare verb. This is mostly consistent with a minor deviation.
The set is intentionally small and well-scoped for a source-backed question-answering server: ingestion, listing, and querying are the three core operations. Each tool earns its place and three tools fit within the recommended range.
The surface covers adding sources, listing them, and asking grounded questions, but lacks update/delete operations and a way to inspect or retrieve an individual source's contents. These are notable lifecycle gaps, though the core ask workflow is present.