notebooklm-mcp-rpc

Import selected research results

research_import_selected

Import specific research results by URL to skip irrelevant sources from a fast-research result set. Pass full URLs or specify a taskId to import from a previous task.

Instructions

Import a subset of research results by URL. Useful when you want to skip irrelevant sources from a fast-research result set. Pass either the full URLs to import, or pass taskId explicitly if you want to import from a non-latest task.

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>",
      "urls": "<urls>"
    },
    "name": "research_import_selected"
  }
}

Input Schema

Name	Required	Description
`urls`	Yes	URLs of the result entries to import.
`taskId`	No	Override the task ID; defaults to the latest task with results.
`notebook`	Yes	Notebook UUID.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jun 30, 2026

TDQS

A4.2/5.0

Behavior3/5

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

Annotations indicate readOnlyHint=false (write operation) and openWorldHint=true (side effects), which match the 'Import' action. However, the description does not elaborate on potential side effects, idempotency, or error behaviors beyond what annotations already imply.

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 sentences that convey the core function and usage details without any redundant words. Front-loaded with the main action, then explains options.

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?

Given the tool's role in the research workflow and the presence of sibling tools like research_import_all, the description covers the key aspects: purpose, input options, and when to use. Could mention return value or confirmation, but not critical for a write operation.

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

Parameters4/5

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

All three parameters have schema descriptions, and the tool description adds clarity by explaining the relationship between taskId and URLs, and the use case for taskId. This enriches the parameter semantics 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?

The description clearly states the tool imports a subset of research results by URL, distinguishing it from the sibling 'research_import_all' which imports all results.

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?

Explicitly says 'Useful when you want to skip irrelevant sources from a fast-research result set', providing a clear scenario. Also explains how to specify inputs (URLs or taskId). Could improve by explicitly mentioning when not to use, but the context implies alternatives.

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

Deploy Server