Skip to main content
Glama
SantosRojas

notebooklm-mcp-pro

by SantosRojas

ask_notebook

Ask a NotebookLM notebook a question to receive a source-cited answer, optionally restricted to specific sources or tied to a prior conversation for follow-ups.

Instructions

Pregunta al notebook y devuelve respuesta con citas a fuentes. Consume cuota de chat y queda en el historial del notebook.

Input Schema

NameRequiredDescriptionDefault
questionYesPregunta; NotebookLM responde solo con base en las fuentes.
source_idsNoRestringe la respuesta a estas fuentes.
notebook_idYesID del notebook (obtenlo con list_notebooks).
conversation_idNoID devuelto antes, para repreguntar con contexto.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already flag readOnlyHint=false, openWorld=true, idempotent=false. The description adds genuinely useful side-effect context beyond those: it consumes chat quota and persists in the notebook history — exactly the non-obvious costs an agent needs before calling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tight sentences with zero filler, front-loading the primary action and return, then appending the cost/side-effect note. Every clause earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, return values needn't be explained, and the schema fully covers parameters. The description adds the quota/history cost, making it complete for correct invocation, only lacking when-to-use guidance versus siblings.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so all four parameters (question, source_ids, notebook_id, conversation_id) are already documented in the schema, including usage hints like obtaining notebook_id via list_notebooks. The description adds nothing beyond it, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (pregunta/ask) and resource (notebook) plus the return format (respuesta con citas a fuentes). This distinguishes it from retrieval siblings like read_source or search_sources, though it doesn't name siblings explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied — you ask the notebook when you want a synthesized, cited answer. But it doesn't state when to prefer this over search_sources, keyword_search, or get_chat_history, and gives no prerequisites or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.