NotebookLM MCP

Create slide deck

slide_deck_create

Generate a PDF slide deck from a NotebookLM notebook's sources after confirming options; set confirm=true to start, then poll studio_status for the download URL.

Instructions

Start generating a slide deck from the notebook's sources. Uses the user's NotebookLM quota and takes several minutes, so agree on the options with the user first: with confirm=false it does nothing and returns pending_confirmation. With confirm=true it returns the artifact_id; poll studio_status until that artifact is completed. Once completed, studio_status gives a download_url for the deck as a PDF.

Input Schema

Name	Required	Description
`format`	No	Format: detailed_deck, presenter_slides
`length`	No	Length: default, short
`confirm`	Yes	Must be true to start generation. With false the tool only returns pending_confirmation and does nothing
`language`	No	BCP-47 language code such as en, es or fr; omit for NotebookLM's default
`source_ids`	No	Limit generation to these source IDs (from notebook_get); omit to use every source in the notebook
`notebook_id`	Yes	Notebook ID, as returned by notebook_list or notebook_create
`focus_prompt`	No	Optional instruction on what to focus on or emphasise, e.g. "the methodology section"

Output Schema

Name	Required	Description
`status`	Yes
`message`	No	Human-readable outcome or next step
`artifact_id`	No	ID of the new artifact, as listed by studio_status

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": {
+    "artifact_id": {
+      "description": "ID of the new artifact, as listed by studio_status",
+      "type": "string"
+    },
+    "message": {
+      "description": "Human-readable outcome or next step",
+      "type": "string"
+    },
+    "status": {
+      "enum": [
+        "success",
+        "pending_confirmation"
+      ],
+      "type": "string"
+    }
+  },
+  "required": [
+    "status"
+  ],
+  "type": "object"
+}

Changed5 schema fields changedv0.4.0Oct 20, 2026

changedInput schema / properties / confirm / description

Previous value: -"Must be true to start generation"New value: +"Must be true to start generation. With false the tool only returns pending_confirmation and does nothing"

changedInput schema / properties / focus_prompt / description

Previous value: -"Focus prompt"New value: +"Optional instruction on what to focus on or emphasise, e.g. \"the methodology section\""

changedInput schema / properties / language / description

Previous value: -"BCP-47 language code"New value: +"BCP-47 language code such as en, es or fr; omit for NotebookLM's default"

changedInput schema / properties / notebook_id / description

Previous value: -"The notebook ID"New value: +"Notebook ID, as returned by notebook_list or notebook_create"

changedInput schema / properties / source_ids / description

Previous value: -"Source IDs (omit for all)"New value: +"Limit generation to these source IDs (from notebook_get); omit to use every source in the notebook"

First observedv0.3.1Aug 6, 2026

TDQS

A4.2/5.0

Behavior3/5

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

The description adds real behavioral context beyond the annotations: it warns that generation consumes the user's NotebookLM quota and takes several minutes, and it explains the confirm=false no-op versus confirm=true commit and the required polling loop with download_url. It does not, however, state whether a started generation can be cancelled or how duplicate calls behave, so there is room beyond a 3 but it is not exhaustive.

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?

Purpose is front-loaded, followed by a cost/latency warning and then the confirm workflow. Every sentence carries actionable information with no filler.

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?

For an async, quota-consuming generation tool this covers the critical path (confirm gate, artifact_id, polling via studio_status, PDF download). An output schema exists so return values need not be detailed, though cancellation/error-recovery behavior is not addressed.

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 the baseline is 3. The description's confirm detail largely restates the schema ('Must be true to start generation. With false the tool only returns pending_confirmation and does nothing') and it says nothing about format, length, language, source_ids, or focus_prompt, so it adds little parameter meaning beyond the schema.

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 ('Start generating a slide deck from the notebook's sources'), and the resource is inherently distinct from the other studio artifacts (audio_overview_create, video_overview_create, infographic_create, report_create). An agent can identify exactly what this produces without opening the schema.

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 explicit pre-conditions and a workflow: agree on options with the user first, use confirm=false to preview, confirm=true to commit, then poll studio_status for completion. This is unambiguous when-to-use and what-to-do-next guidance.

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