Skip to main content
Glama
rubayatkhan

mcp-research-pipeline

by rubayatkhan

add_source

Add a URL, YouTube video, or raw text to a NotebookLM notebook for research. Specify the notebook ID and source type to ingest content into your research pipeline.

Instructions

Add a source to a NotebookLM notebook.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
waitNoIf true, wait for the source to finish processing (default: true).
valueYesThe URL, YouTube URL, or raw text content to add.
notebook_idYesID of the target notebook.
source_typeYesOne of "url", "youtube", or "text".

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It merely restates the action and does not mention that adding a source may trigger asynchronous processing, that the wait parameter controls that behavior, or that the operation modifies an existing notebook. This is a significant gap for a mutation tool.

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 a single direct sentence with no filler, repetition, or irrelevant detail. It front-loads the action and target clearly, which is an excellent example of conciseness even though other dimensions lack depth.

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

Completeness3/5

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

The schema is rich and an output schema exists, so return-value documentation is not needed from the description. However, with no annotations and only a one-line description, the agent is left without guidance on usage context, processing behavior, or when to set wait to false. It is minimally viable but not fully complete.

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 input schema already documents all four parameters with meaningful descriptions. The description adds no additional parameter semantics, so the baseline score of 3 is appropriate.

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

Purpose4/5

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

The description clearly states the action and target: 'Add a source to a NotebookLM notebook.' It is not a tautology and conveys the core operation, but it does not explicitly differentiate itself from sibling tools like research_topic or list_sources beyond the obvious verb and resource.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives, when not to use it, or any prerequisites. Usage context is only implied by the verb 'add' and the resource 'source,' which is not enough to help an agent choose among the rich sibling tool set.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/rubayatkhan/mcp-research-pipeline'

If you have feedback or need assistance with the MCP directory API, please join our Discord server