NotebookLM MCP

Summarise notebook

notebook_summarize

Read-onlyIdempotent

Get oriented in an unfamiliar NotebookLM notebook: generate an AI overview, source coverage summary, and suggested questions to ask.

Instructions

Ask NotebookLM for an AI-generated overview of the whole notebook. Returns a short summary of what its sources cover and the questions NotebookLM suggests asking about them. Use it to get oriented in an unfamiliar notebook; ask specific questions with notebook_query and list the sources with notebook_get.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`notebook_id`	Yes	Notebook ID, as returned by notebook_list or notebook_create

Output Schema

TableJSON Schema

Name	Required	Description
`status`	Yes
`message`	No	Human-readable outcome or next step
`summary`	Yes	Overview of what the sources cover
`suggested_questions`	Yes	Questions NotebookLM suggests asking with notebook_query

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.5.0Oct 20, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "message": {
+      "description": "Human-readable outcome or next step",
+      "type": "string"
+    },
+    "status": {
+      "const": "success",
+      "type": "string"
+    },
+    "suggested_questions": {
+      "description": "Questions NotebookLM suggests asking with notebook_query",
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "summary": {
+      "description": "Overview of what the sources cover",
+      "type": "string"
+    }
+  },
+  "required": [
+    "status",
+    "summary",
+    "suggested_questions"
+  ],
+  "type": "object"
+}

Addedv0.4.0Oct 20, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, openWorld), so the bar is lower. The description still adds non-obvious behavior: the output is AI-generated, contains the notebook's coverage plus NotebookLM's suggested follow-up questions, and is a whole-notebook (not per-source) view. That is real context beyond the annotations and output schema.

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?

Three tight sentences, front-loaded with the action, then the return content, then the routing guidance. Every sentence carries information an agent needs; nothing is decorative.

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

Completeness5/5

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

For a one-parameter, read-only tool with an output schema and full annotation coverage, the description supplies everything still needed: what it does, what it returns conceptually, and when to prefer siblings. No material gap remains.

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?

A single parameter with 100% schema description coverage, so the schema already documents notebook_id and its provenance (notebook_list / notebook_create). The description adds no syntax or format detail beyond that. Baseline 3 is correct when the schema does the heavy lifting.

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

Purpose5/5

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

States a specific verb and resource ("AI-generated overview of the whole notebook") and explicitly scopes it to the entire notebook rather than individual sources or targeted Q&A. It distinguishes itself from notebook_query and notebook_get by name, so an agent can route without opening schemas.

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

Usage Guidelines5/5

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

Gives an explicit positive trigger ("use it to get oriented in an unfamiliar notebook") and names two alternatives with their own conditions: notebook_query for specific questions, notebook_get for listing sources. Nothing is left to inference.

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