notebooklm-mcp-rpc

Generate a video overview

generate_video

Start video generation from a NotebookLM notebook. Configure format, style, language, and source filters. After submission, use artifact_wait to retrieve the completed video.

Instructions

Kick off video generation. Long-running (15-45 min) — use artifact_wait separately.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "notebook": "<notebook>"
    },
    "name": "generate_video"
  }
}

Input Schema

Name	Required	Description
`style`	No
`format`	No
`language`	No	Output language code (e.g. en, ja, zh_Hans).
`notebook`	Yes	Notebook UUID.
`sourceIds`	No	Restrict generation to these source IDs.
`instructions`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jun 30, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Annotations indicate a write operation (readOnlyHint=false) and openWorldHint=true. The description adds valuable behavioral context: the task is long-running (15-45 min) and requires a separate wait step. No contradictions with annotations.

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?

The description is extremely concise—two sentences with no fluff. It front-loads the key action and critical behavioral note, earning every word.

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

Completeness2/5

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

Given the complexity (6 parameters, no output schema), the description is insufficient. It omits parameter explanations, return value expectations, and behavior on multiple calls. The long-running note is helpful but incomplete.

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

Parameters2/5

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

Schema coverage is 50% (3 of 6 parameters have descriptions). The description does not add any parameter-level meaning, leaving half the parameters (style, format, instructions) unexplained. This does not compensate for the missing schema details.

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?

The description clearly states the verb 'Kick off video generation' and the resource 'video overview'. It distinguishes itself from sibling tools by noting the long-running nature and the need to use artifact_wait separately.

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

Usage Guidelines4/5

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

The description explicitly provides guidance on when to use this tool (to start video generation) and what to do after (use artifact_wait). However, it does not explicitly contrast with alternative tools like generate_cinematic_video.

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

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