notebooklm-mcp-cli

Research Import

research_import

Import discovered sources into a notebook after research completes. Use with a completed research task to add its sources to your notebook.

Instructions

Import discovered sources into notebook.

Call after research_status shows status="completed".

Input Schema

TableJSON Schema

Name	Required	Description
`task_id`	Yes	Research task ID
`timeout`	No	Import timeout in seconds (default: 300, increase for large notebooks)
`cited_only`	No	Import only sources cited by the research report. Overrides source_indices when enabled.
`notebook_id`	Yes	Notebook UUID
`source_indices`	No	Source indices to import (default: all)

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.11.5Sep 18, 2026

TDQS

A4/5.0

Behavior3/5

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

With no annotations, the description carries the behavioral burden. It discloses the key prerequisite and clearly implies a mutating import, but it does not describe idempotency, duplicate handling, or other side effects on the notebook. This is adequate but not deeply transparent.

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 two concise sentences: the first states the action, the second gives an operational precondition. Every sentence earns its place 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?

The description covers the essential workflow context and the full parameter schema plus output schema handle the structural details. It lacks discussion of idempotency or duplicate imports, but these are not critical given the rich structured metadata.

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% and all parameters already have descriptive text. The tool description itself adds no parameter-level meaning, so the baseline of 3 applies.

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 states a specific verb ('Import'), object ('discovered sources'), and destination ('notebook'), which clearly differentiates this from research_start and research_status. The purpose is unambiguous.

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?

It provides an explicit workflow precondition: 'Call after research_status shows status="completed"'. This tells the agent when to invoke the tool, but it does not name alternative tools or explicitly state when-not-to-use.

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